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DBMS > Greenplum vs. InfinityDB vs. IRONdb vs. Percona Server for MongoDB vs. Spark SQL

System Properties Comparison Greenplum vs. InfinityDB vs. IRONdb vs. Percona Server for MongoDB vs. Spark SQL

Editorial information provided by DB-Engines
NameGreenplum  Xexclude from comparisonInfinityDB  Xexclude from comparisonIRONdb  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.A Java embedded Key-Value Store which extends the Java Map interfaceA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA drop-in replacement for MongoDB Community Edition with enterprise-grade features.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeTime Series DBMSDocument storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.23
Rank#47  Overall
#30  Relational DBMS
Score0.07
Rank#359  Overall
#54  Key-value stores
Score0.55
Rank#253  Overall
#39  Document stores
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitegreenplum.orgboilerbay.comwww.circonus.com/solutions/time-series-database/www.percona.com/­mongodb/­software/­percona-server-for-mongodbspark.apache.org/­sql
Technical documentationdocs.greenplum.orgboilerbay.com/­infinitydb/­manualdocs.circonus.com/irondb/category/getting-starteddocs.percona.com/­percona-distribution-for-mongodbspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperPivotal Software Inc.Boiler Bay Inc.Circonus LLC.PerconaApache Software Foundation
Initial release20052002201720152014
Current release7.0.0, September 20234.0V0.10.20, January 20183.4.10-2.10, November 20173.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoGPL Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C++Scala
Server operating systemsLinuxAll OS with a Java VMLinuxLinuxLinux
OS X
Windows
Data schemeyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes infotext, numeric, histogramsyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yes infosince Version 4.2nononono
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilitynoyesno
SQL infoSupport of SQLyesnoSQL-like query language (Circonus Analytics Query Language: CAQL)noSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP APIproprietary protocol using JSONJDBC
ODBC
Supported programming languagesC
Java
Perl
Python
R
Java.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnoyes, in LuaJavaScriptno
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneAutomatic, metric affinity per nodeShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneconfigurable replication factor, datacenter awareSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate consistency per node, eventual consistency across nodesEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesno infomanual creation possible, using inversions based on multi-value capabilitynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes infovia In-Memory Engineno
User concepts infoAccess controlfine grained access rights according to SQL-standardnonoAccess rights for users and rolesno

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More resources
GreenplumInfinityDBIRONdbPercona Server for MongoDBSpark SQL
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