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• Performance of java on different hardware?

  - by tangens

  In another SO question I asked why my java programs run faster on AMD than on Intel machines. But it seems that I'm the only one who has observed this. Now I would like to invite you to share the numbers of your local java performance with the SO community. I observed a big performance difference when watching the startup of JBoss on different hardware, so I set this program as the base for this comparison. For participation please download JBoss 5.1.0.GA and run: jboss-5.1.0.GA/bin/run.sh (or run.bat) This starts a standard configuration of JBoss without any extra applications. Then look for the last line of the start procedure which looks like this: [ServerImpl] JBoss (Microcontainer) [5.1.0.GA (build: SVNTag=JBoss_5_1_0_GA date=200905221634)] Started in 25s:264ms Please repeat this procedure until the printed time is somewhat stable and post this line together with some comments on your hardware (I used cpu-z to get the infos) and operating system like this: java version: 1.6.0_13 OS: Windows XP Board: ASUS M4A78T-E Processor: AMD Phenom II X3 720, 2.8 GHz RAM: 2*2 GB DDR3 (labeled 1333 MHz) GPU: NVIDIA GeForce 9400 GT disc: Seagate 1.5 TB (ST31500341AS) Use your votes to bring the fastest configuration to the top. I'm very curious about the results. EDIT: Up to now only a few members have shared their results. I'd really be interested in the results obtained with some other architectures. If someone works with a MAC (desktop) or runs an Intel i7 with less than 3 GHz, please once start JBoss and share your results. It will only take a few minutes.

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• Memory Bandwidth Performance for Modern Machines

  - by porgarmingduod

  I'm designing a real-time system that occasionally has to duplicate a large amount of memory. The memory consists of non-tiny regions, so I expect the copying performance will be fairly close to the maximum bandwidth the relevant components (CPU, RAM, MB) can do. This led me to wonder what kind of raw memory bandwidth modern commodity machine can muster? My aging Core2Duo gives me 1.5 GB/s if I use 1 thread to memcpy() (and understandably less if I memcpy() with both cores simultaneously.) While 1.5 GB is a fair amount of data, the real-time application I'm working on will have have something like 1/50th of a second, which means 30 MB. Basically, almost nothing. And perhaps worst of all, as I add multiple cores, I can process a lot more data without any increased performance for the needed duplication step. But a low-end Core2Due isn't exactly hot stuff these days. Are there any sites with information, such as actual benchmarks, on raw memory bandwidth on current and near-future hardware? Furthermore, for duplicating large amounts of data in memory, are there any shortcuts, or is memcpy() as good as it will get? Given a bunch of cores with nothing to do but duplicate as much memory as possible in a short amount of time, what's the best I can do?

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• Lucene (.NET) Document stucture and performance suggestions.

  - by Josh Handel

  Hello, I am indexing about 100M documents that consist of a few string identifiers and a hundred or so numaric terms.. I won't be doing range queries, so I haven't dugg too deep into Numaric Field but I'm not thinking its the right choose here. My problem is that the query performance degrades quickly when I start adding OR criteria to my query.. All my queries are on specific numaric terms.. So a document looks like StringField:[someString] and N DataField:[someNumber].. I then query it with something like DataField:((+1 +(2 3)) (+75 +(3 5 52)) (+99 +88 +(102 155 199))). Currently these queries take about 7 to 16 seconds to run on my laptop.. I would like to make sure thats really the best they can do.. I am open to suggestions on field structure and query structure :-). Thanks Josh PS: I have already read over all the other lucene performance discussions on here, and on the Lucene wiki and at lucid imiagination... I'm a bit further down the rabbit hole then that...

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• Testing performance of queries in mysl

  - by Unreason

  I am trying to setup a script that would test performance of queries on a development mysql server. Here are more details: I have root access I am the only user accessing the server Mostly interested in InnoDB performance The queries I am optimizing are mostly search queries (SELECT ... LIKE '%xy%') What I want to do is to create reliable testing environment for measuring the speed of a single query, free from dependencies on other variables. Till now I have been using SQL_NO_CACHE, but sometimes the results of such tests also show caching behaviour - taking much longer to execute on the first run and taking less time on subsequent runs. If someone can explain this behaviour in full detail I might stick to using SQL_NO_CACHE; I do believe that it might be due to file system cache and/or caching of indexes used to execute the query, as this post explains. It is not clear to me when Buffer Pool and Key Buffer get invalidated or how they might interfere with testing. So, short of restarting mysql server, how would you recommend to setup an environment that would be reliable in determining if one query performs better then the other?

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• Divide and conquer of large objects for GC performance

  - by Aperion

  At my work we're discussing different approaches to cleaning up a large amount of managed ~50-100MB memory.There are two approaches on the table (read: two senior devs can't agree) and not having the experience the rest of the team is unsure of what approach is more desirable, performance or maintainability. The data being collected is many small items, ~30000 which in turn contains other items, all objects are managed. There is a lot of references between these objects including event handlers but not to outside objects. We'll call this large group of objects and references as a single entity called a blob. Approach #1: Make sure all references to objects in the blob are severed and let the GC handle the blob and all the connections. Approach #2: Implement IDisposable on these objects then call dispose on these objects and set references to Nothing and remove handlers. The theory behind the second approach is since the large longer lived objects take longer to cleanup in the GC. So, by cutting the large objects into smaller bite size morsels the garbage collector will processes them faster, thus a performance gain. So I think the basic question is this: Does breaking apart large groups of interconnected objects optimize data for garbage collection or is better to keep them together and rely on the garbage collection algorithms to processes the data for you? I feel this is a case of pre-optimization, but I do not know enough of the GC to know what does help or hinder it.

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• Performance Difference between HttpContext user and Thread user

  - by atrueresistance

  I am wondering what the difference between HttpContext.Current.User.Identity.Name.ToString.ToLower and Thread.CurrentPrincipal.Identity.Name.ToString.ToLower. Both methods grab the username in my asp.net 3.5 web service. I decided to figure out if there was any difference in performance using a little program. Running from full Stop to Start Debugging in every run. Dim st As DateTime = DateAndTime.Now Try 'user = HttpContext.Current.User.Identity.Name.ToString.ToLower user = Thread.CurrentPrincipal.Identity.Name.ToString.ToLower Dim dif As TimeSpan = Now.Subtract(st) Dim break As String = "nothing" Catch ex As Exception user = "Undefined" End Try I set a breakpoint on break to read the value of dif. The results were the same for both methods. dif.Milliseconds 0 Integer dif.Ticks 0 Long Using a longer duration, loop 5,000 times results in these figures. Thread Method run 1 dif.Milliseconds 125 Integer dif.Ticks 1250000 Long run 2 dif.Milliseconds 0 Integer dif.Ticks 0 Long run 3 dif.Milliseconds 0 Integer dif.Ticks 0 Long HttpContext Method run 1 dif.Milliseconds 15 Integer dif.Ticks 156250 Long run 2 dif.Milliseconds 156 Integer dif.Ticks 1562500 Long run 3 dif.Milliseconds 0 Integer dif.Ticks 0 Long So I guess what is more prefered, or more compliant with webservice standards? If there is some type of a performance advantage, I can't really tell. Which one scales to larger environments easier?

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• SQL Server performance issue.

  - by Jit

  Hi Friends, I have been trying to analyze performance issue with SQL Server 2005. We have 30 jobs, one for each databases (30 databases, one per each client). The jobs run at early morning at an interval of 5 minutes. When I run the job individually for testing, for most of the databases it finishes in 7 to 9 minutes. But when these jobs run at early morning, I see few jobs taking 2 to 3 hours to finish and the same takes few minutes as mentioned above if ran independently. We dont have any other job scheduled during that time, other than these 30 jobs. If we restart the server then for 2 or so days all the jobs finishes in few minutes, but over the period of time (from 3rd day suddenly), few jobs start taking hours to finish. What could be the possible reason of performance degradation over the period of time? I verified all the SPs and we uses temp tables and I made sure none of the temp table is left without dropping at the end of SP. Let me know what are the possible reasons for such behavior. Appreciate your time and help. Thanks

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• Poor performance using RMI-proxies with Swing components

  - by Patrick

  I'm having huge performance issues when I add RMI proxy references to a Java Swing JList-component. I'm retrieving a list of user Profiles with RMI from a server. The retrieval itself takes just a second or so, so that's acceptable under the circumstances. However, when I try to add these proxies to a JList, with the help of a custom ListModel and a CellRenderer, it takes between 30-60 seconds to add about 180 objects. Since it is a list of users' names, it's preferrable to present them alphabetically. The biggest performance hit is when I sort the elements as they get added to the ListModel. Since the list will always be sorted, I opted to use the built-in Collections.binarySearch() to find the correct position for the next element to be added, and the comparator uses two methods that are defined by the Profile interface, namely getFirstName() and getLastName(). Is there any way to speed this process up, or am I simply implementing it the wrong way? Or is this a "feature" of RMI? I'd really love to be able to cache some of the data of the remote objects locally, to minimize the remote method calls.

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• Google app engine: Poor Performance with JDO + Datastore

  - by Bosh

  I have a simple data model that includes USERS: store basic information (key, name, phone # etc) RELATIONS: describe, e.g. a friendship between two users (supplying a relationship_type + two user keys) I'm getting very poor performance, for instance, if I try to print the first names of all of a user's friends. Say the user has 500 friends: I can fetch the list of friend user_ids very easily in a single query. But then, to pull out first names, I have to do 500 back-and-forth trips to the Datastore, each of which seems to take on the order of 30 ms. If this were SQL, I'd just do a JOIN and get the answer out fast. I understand there are rudimentary facilities for performing joins across un-owned relations in a relaxed implementation of JDO (as described at http://gae-java-persistence.blogspot.com) but they sound experimental and non-standard (e.g. my code won't work in any other JDO implementation). Is this really my best bet? Otherwise, how do people extract satisfactory performance from JDO/Datastore in this kind of (very common) situation? -Bosh

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• Silverlight performance with many loaded controls

  - by gius

  I have a SL application with many DataGrids (from Silverlight Toolkit), each on its own view. If several DataGrids are opened, changing between views (TabItems, for example) takes a long time (few seconds) and it freezes the whole application (UI thread). The more DataGrids are loaded, the longer the change takes. These DataGrids that slow the UI chanage might be on other places in the app and not even visible at that moment. But once they are opened (and loaded with data), they slow showing other DataGrids. Note that DataGrids are NOT disposed and then recreated again, they still remain in memory, only their parent control is being hidden and visible again. I have profiled the application. It shows that agcore.dll's SetValue function is the bottleneck. Unfortunately, debug symbols are not available for this Silverlight native library responsible for drawing. The problem is not in the DataGrid control - I tried to replace it with XCeed's grid and the performance when changing views is even worse. Do you have any idea how to solve this problem? Why more opened controls slow down other controls? I have created a sample that shows this issue: http://cenud.cz/PerfTest.zip UPDATE: Using VS11 profiler on the sample provided suggests that the problem could be in MeasureOverride being called many times (for each DataGridCell, I guess). But still, why is it slower as more controls are loaded elsewhere? Is there a way to improve the performance?

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• Reduce durability in MySQL for performance

  - by Paul Prescod

  My site occasionally has fairly predictable bursts of traffic that increase the throughput by 100 times more than normal. For example, we are going to be featured on a television show, and I expect in the hour after the show, I'll get more than 100 times more traffic than normal. My understanding is that MySQL (InnoDB) generally keeps my data in a bunch of different places: RAM Buffers commitlog binary log actual tables All of the above places on my DB slave This is too much "durability" given that I'm on an EC2 node and most of the stuff goes across the same network pipe (file systems are network attached). Plus the drives are just slow. The data is not high value and I'd rather take a small chance of a few minutes of data loss rather than have a high probability of an outage when the crowd arrives. During these traffic bursts I would like to do all of that I/O only if I can afford it. I'd like to just keep as much in RAM as possible (I have a fair chunk of RAM compared to the data size that would be touched over an hour). If buffers get scarce, or the I/O channel is not too overloaded, then sure, I'd like things to go to the commitlog or binary log to be sent to the slave. If, and only if, the I/O channel is not overloaded, I'd like to write back to the actual tables. In other words, I'd like MySQL/InnoDB to use a "write back" cache algorithm rather than a "write through" cache algorithm. Can I convince it to do that? If this is not possible, I am interested in general MySQL write-performance optimization tips. Most of the docs are about optimizing read performance, but when I get a crowd of users, I am creating accounts for all of them, so that's a write-heavy workload.

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• Displaying performance metrics in a modern web app?

  - by Charles

  We're updating our ancient internal PHP application at work. Right now, we gather extensive performance measurements on every pageview, and log them to the database. Additionally, users requested that some of the metrics be displayed at the bottom of the page. This worked out pretty well for us, because the last thing that the application does on every request is include the file containing the HTML footer. The updated parts of the application use an MVC framework and a Dispatch/Request/Response loop. The page footer is no longer the last thing done. In fact, it could very well be the first thing done, before the rest of the page is created. Because we can grab the Response before it's returned to the user, we could try to include placeholders for the performance metrics in the footer and simply replace them with the actual numbers, but this strikes me as a bad idea somehow. How do you handle this in your modern web app? While we're using PHP, I'm curious how it's done in a Ruby/Rails app, and in your favorite Python framework.

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• PHP: Opening/closing tags & performance?

  - by Tom

  Hi, This may be a silly question, but as someone relatively new to PHP, I'm wondering if there are any performance-related issues to frequently opening and closing PHP tags in HTML template code, and if so, what might be best practices in terms of working with php tags? My question is not about the importance/correctness of closing tags, or about which type of code is more readable than another, but rather about how the document gets parsed/executed and what impact it might have on performance. To illustrate, consider the following two extremes: Mixing PHP and HTML tags: <?php echo '<tr> <td>'.$variable1.'</td> <td>'.$variable2.'</td> <td>'.$variable3.'</td> <td>'.$variable4.'</td> <td>'.$variable5.'</td> </tr>' ?> // PHP tag opened once Separating PHP and HTML tags: <tr> <td><?php echo $variable1 ?></td> <td><?php echo $variable2 ?></td> <td><?php echo $variable3 ?></td> <td><?php echo $variable4 ?></td> <td><?php echo $variable5 ?></td> </tr> // PHP tag opened five times Would be interested in hearing some views on this, even if it's just to hear that it makes no difference. Thanks.

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• Performance Problems with Django's F() Object

  - by JayhawksFan93

  Has anyone else noticed performance issues using Django's F() object? I am running Windows XP SP3 and developing against the Django trunk. A snippet of the models I'm using and the query I'm building are below. When I have the F() object in place, each call to a QuerySet method (e.g. filter, exclude, order_by, distinct, etc.) takes approximately 2 seconds, but when I comment out the F() clause the calls are sub-second. I had a co-worker test it on his Ubuntu machine, and he is not experiencing the same performance issues I am with the F() clause. Anyone else seeing this behavior? class Move (models.Model): state_meaning = models.CharField( max_length=16, db_index=True, blank=True, default='' ) drop = models.ForeignKey( Org, db_index=True, null=False, default=1, related_name='as_move_drop' ) class Split(models.Model): state_meaning = models.CharField( max_length=16, db_index=True, blank=True, default='' ) move = models.ForeignKey( Move, related_name='splits' ) pickup = models.ForeignKey( Org, db_index=True, null=False, default=1, related_name='as_split_pickup' ) pickup_date = models.DateField( null=True, default=None ) drop = models.ForeignKey( Org, db_index=True, null=False, default=1, related_name='as_split_drop' ) drop_date = models.DateField( null=True, default=None, db_index=True ) def get_splits(begin_date, end_date): qs = Split.objects \ .filter(state_meaning__in=['INPROGRESS','FULFILLED'], drop=F('move__drop'), # <<< the line in question pickup_date__lte=end_date) elapsed = timer.clock() - start print 'qs1 took %.3f' % elapsed start = timer.clock() qs = qs.filter(Q(drop_date__gte=begin_date) | Q(drop_date__isnull=True)) elapsed = timer.clock() - start print 'qs2 took %.3f' % elapsed start = timer.clock() qs = qs.exclude(move__state_meaning='UNFULFILLED') elapsed = timer.clock() - start print 'qs3 took %.3f' % elapsed start = timer.clock() qs = qs.order_by('pickup_date', 'drop_date') elapsed = timer.clock() - start print 'qs7 took %.3f' % elapsed start = timer.clock() qs = qs.distinct() elapsed = timer.clock() - start print 'qs8 took %.3f' % elapsed

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• performance issue: difference between select s.* vs select *

  - by kamil

  Recently I had some problem in performance of my query. The thing is described here: poor Hibernate select performance comparing to running directly - how debug? After long time of struggling, I've finally discovered that the query with select prefix like: select sth.* from Something as sth... Is 300x times slower then query started this way: select * from Something as sth.. Could somebody help me, and asnwer why is that so? Some external documents on this would be really useful. The table used for testing was: SALES_UNIT table contains some basic info abot sales unit node such as name and etc. The only association is to table SALES_UNIT_TYPE, as ManyToOne. The primary key is ID and field VALID_FROM_DTTM which is date. SALES_UNIT_RELATION contains relation PARENT-CHILD between sales unit nodes. Consists of SALES_UNIT_PARENT_ID, SALES_UNIT_CHILD_ID and VALID_TO_DTTM/VALID_FROM_DTTM. No association with any tables. The PK here is ..PARENT_ID, ..CHILD_ID and VALID_FROM_DTTM The actual query I've done was: select s.* from sales_unit s left join sales_unit_relation r on (s.sales_unit_id = r.sales_unit_child_id) where r.sales_unit_child_id is null select * from sales_unit s left join sales_unit_relation r on (s.sales_unit_id = r.sales_unit_child_id) where r.sales_unit_child_id is null Same query, both uses left join and only difference is with select.

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• Force database read to master if slave data is stale

  - by Jeff Storey

  I previously asked a specific question about this database replication for new user signup to which I got an answer, but I want to ask this in the more general sense. I have a database setup in which I am using a master/slave combination. I am using the slaves for load balancing (the data itself is partitioned/sharded across multiple databases, but each database has X slaves for load balancing). Let's say I write some data to the master. Now I do a subsequent read which hits a slave, but the slave has not yet caught up to the master. Is there a way (which can be done quickly since it will happen frequently) to determine if the data is stale in the slave so I can then route to the master? In my previous question, it was suggested to do simultaneous writes to the cache and the database. This solution seems practical, but there is still a chance that the data may have been removed from the cache but not yet updated in the slave. A possible solution is to ensure the cache is big enough (based on the typical application load) so the data will not be evicted within the time frame it takes to replicate the data. This seems like it may be feasible. Can anyone provide additional insight into this question? Thanks!

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• How to back up a database with thousands of files

  - by Neal

  I am working with a Fedora server that runs a customized software package. The server software is quite old, and its database consists of 1,723 files. The database files are constantly changing - they continually grow and changes are not necessarily appended to the end. So right now, we currently back up every 24 hours at midnight when all users are off of the system and the database is in an internally consistent state. The problem is that we have the potential to lose an entire day's worth of work, which would be unrecoverable. So I'd like to know if there is a way to take some sort of an instantaneous snapshot of these database files that we could back up every 30 minutes or so. I've read about Linux LVM snapshots, and am thinking that I might be able to do accomplish the goal by taking a snapshot, rsync'ing the files to a backup server, then dropping the snapshot. But I've never done this before,so I don't know if this is the "right" fix. Any ideas on this? Any better solutions? Thanks!

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• Synchronize Active Directory to Database

  - by Tommy Jakobsen

  We are in a situation where we would like to offer our customers to be able to manage their users themselves. It is around 300 customers with up to a total of 10.000 users. Besides creating, updating and removing users, they will very often read information about users for statics and other useful informations available. All this functionality, should be available from an Intranet web page (.NET Framework 4) that the users will access through Citrix or similar. Now the problem is that we would really like the users not to query AD directly for each request, but rather make them hit a database that is synchronized with AD. It would be sufficient to run this synchronization a few time each day (maybe every 5. hour). When they create a user, it should not be available right away, but reviewed and then created within two days (the next step would be to remove this manual review, but that's out of scope for this question). What do you think about this synchronization of AD? Does anyone have any experience with it and is it something that is done in other organizations, where you will have lots of requests which is better handled by a database than AD (I presume)? Are there any techniques out there for writing such a script that synchronizes AD with database tables? My primary concern is the groups/members relations which can be rather complicated. Or are there software that synchronizes AD with a database? Any comments will be much appreciated. Thank you.

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• PyQt error: QSqlDatabasePrivate::database: unable to open database

  - by DSblizzard

  What is the cause of following error: QSqlDatabasePrivate::database: unable to open database: unable to open database file Error opening database? Code is 100% correct, this message appeared when I have reinstalled Windows, Python and PyQt.

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• Oracle OpenWorld 2012: Focus On Oracle Database

  - by jgelhaus

  As Oracle OpenWorld approaches and you work to plan your schedule.  We know there's a lot to sort through.  To help we've put together some Oracle Database Focus On Documents to help guide you through the database sessions at the show. Oracle Database Oracle Database Application Development Oracle Database Security Oracle Spatial and Graph Oracle Enterprise Manager Cloud Control 12c (and Private Cloud) Big Data Oracle Exadata Data Warehousing High Availability Oracle Database Utilities Oracle Database Upgrade See you in San Francisco!

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• Oracle Database Express Edition, már 64 bitesen is

  - by user645740

  Az Oracle Database Express Edition egy ingyenes adatbázis-kezelo, amivel ki lehet ingyen próbálni az Oracle Database-t. Support viszont nem áll hozzá rendelkezésre, fórumokat lehet használni ehelyett. Az Oracle Database Express Edition 11gR2 most megjelent 64 bites változatban is: http://www.oracle.com/technetwork/database/database-technologies/express-edition/downloads/index.html Az Oracle Database SE One, SE és EE itt érheto el 30 napos kipróbálásra: http://www.oracle.com/technetwork/database/enterprise-edition/downloads/index.html

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• Data in two databases, eager spool resulting in query

  - by Valkyrie

  I have two databases in SQL2k5: one that holds a large amount of static data (SQL Database 1) (never updated but frequently inserted into) and one that holds relational data (SQL Database 2) related to the static data. They're separated mainly because of corporate guidelines and business requirements: assume for the following problem that combining them is not practical. There are places in SQLDB2 that PKs in SQLDB1 are referenced; triggers control the referential integrity, since cross-database relationships are troublesome in SQL Server. BUT, because of the large amount of data in SQLDB1, I'm getting eager spools on queries that join from the Id in SQLDB2 that references the data in SQLDB1. (With me so far? Maybe an example will help:) SELECT t.Id, t.Name, t2.Company FROM SQLDB1.table t INNER JOIN SQLDB2.table t2 ON t.Id = t2.FKId This query results in a eager spool that's 84% of the load of the query; the table in SQLDB1 has 35M rows, so it's completely choking this query. I can't create a view on the table in SQLDB1 and use that as my FK/index; it doesn't want me to create a constraint based on a view. Anyone have any idea how I can fix this huge bottleneck? (Short of putting the static data in the first db: believe me, I've argued that one until I'm blue in the face to no avail.) Thanks! valkyrie Edit: also can't create an indexed view because you can't put schemabinding on a view that references a table outside the database where the view resides. Dang it.

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• question about MySQL database migration

  - by WilliamLou

  Hi there: If I have a MySQL database with several tables on a live server, now I would like to migrate this database to another server. Of course, the migration I mean here involves some database tables, for example: add some new columns to several tables, add some new tables etc.. Now, the only method I can think of is to use some php/python(two scripts I know) script, connect two databases, dump the data from the old database, and then write into the new database. However, this method is not efficient at all. For example: in old database, table A has 28 columns; in new database, table A has 29 columns, but the extra column will have default value 0 for all the old rows. My script still needs to dump the data row by row and insert each row into the new database. Is there any tools or a better method than writing a script yourself? Here, I dont need to worry about multithread writing problems etc.., I mean the old database will be down (not open to public usage etc.., only for upgrade ) for a while. Thanks!!

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• How to store data in mysql, to get the fastest performance?

  - by Oden

  Hey, I'm thinking about it, witch of the following two query types would give me the fastest performance for a user messaging module inside my site: The first one i thought about is a multi table setup, witch has a connection table, and a main table. The connection table holds the connection between accounts, and the messaging table. In this case a query would look like following, to get some data of the author, and the messages he has sent: SELECT m.*, a.username FROM messages AS m LEFT JOIN connection_table ON (message_id = m.id) LEFT JOIN accounts AS a ON (account_id = a.id) WHERE m.id = '32341' Inserting into it is a little bit more "complicated". My other idea, and in my thought the better solution of this problem is that i store the data i would use in a connection table in the same table where is store the data of the mail. Sounds like i would get lots of duplicated entries, but no, because i have a field witch has text type and holds user ids like this: *24*32*249* If I want to query them, i use the mysql LIKE method. Deleting is an other problem, but for this i have one more field where i store who has deleted the post. Sad about that i don't know how to join this. So what would you recommend? Are there other ways?

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• postgreSQL vs Cassandra vs MongoDB vs Voldemart ?

  - by ramonrails

  Which database to decide upon? Any comparisions? Existing: postgresql Issues Not easily scalable horizontal. Needs sharding etc Clustering does not solve the data growth problem Looking for: Any database that is easily horizontally scalable Cassandra (Twitter uses that?) MongoDB (rapidly gaining popularity) Voldemart Other? Why? Data growing with snowball effect existing postgresql locks table etc for vaccuum tasks periodically Archiving data is tideous currently Human interaction involved in existing archive, vaccuum, ... process periodically Need a 'set it. forget it. just add another server when data grows more.' type of solution

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