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

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

Editorial information provided by DB-Engines
NameInfinityDB  Xexclude from comparisonIRONdb  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionA 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 processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelKey-value storeTime Series DBMSDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.04
Rank#326  Overall
#51  Key-value stores
Score0.03
Rank#334  Overall
#33  Time Series DBMS
Score0.63
Rank#215  Overall
#32  Document stores
Score22.94
Rank#34  Overall
#20  Relational DBMS
Score0.08
Rank#310  Overall
#139  Relational DBMS
Websiteboilerbay.comwww.circonus.com/­solutions/­time-series-databasewww.percona.com/­software/­mongodb/­percona-server-for-mongodbspark.apache.org/­sqlwww.transaction.de/­en/­solutions/­transbase-resource-optimized-high-performance-database
Technical documentationboilerbay.com/­infinitydb/­manualdocs.circonus.com/­irondbwww.percona.com/­doc/­percona-server-for-mongodb/­LATEST/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­transbase-inside
DeveloperBoiler Bay Inc.Circonus LLC.PerconaApache Software FoundationTransaction Software GmbH
Initial release20022017201520141987
Current release4.0V0.10.20, January 20183.4.10-2.10, November 20173.2.0, October 2021Transbase 8.4, September 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL Version 2Open Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++C++ScalaC and C++
Server operating systemsAll OS with a Java VMLinuxLinuxLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes infotext, numeric, histogramsyesyesyes
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.nonononono
Secondary indexesno infomanual creation possible, using inversions based on multi-value capabilitynoyesnoyes
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)noSQL-like DML and DDL statementsyes
APIs and other access methodsAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP APIproprietary protocol using JSONJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesJava.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
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnoyes, in LuaJavaScriptnoyes
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesnoneAutomatic, metric affinity per nodeShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnoneconfigurable replication factor, datacenter awareSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate consistency per node, eventual consistency across nodesEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infomanual creation possible, using inversions based on multi-value capabilitynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoOptimistic locking for transactions; no isolation for bulk loadsnononoyes
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.nonoyes infovia In-Memory Enginenono
User concepts infoAccess controlnonoAccess rights for users and rolesnofine grained access rights according to SQL-standard

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More resources
InfinityDBIRONdbPercona Server for MongoDBSpark SQLTransbase
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