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DBMS > EventStoreDB vs. IRONdb vs. Spark SQL vs. Transbase

System Properties Comparison EventStoreDB vs. IRONdb vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines
NameEventStoreDB  Xexclude from comparisonIRONdb  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionIndustrial-strength, open-source database solution built from the ground up for event sourcing.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicitySpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelEvent StoreTime Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.10
Rank#179  Overall
#1  Event Stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitewww.eventstore.comwww.circonus.com/solutions/time-series-database/spark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdevelopers.eventstore.comdocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperEvent Store LimitedCirconus LLC.Apache Software FoundationTransaction Software GmbH
Initial release2012201720141987
Current release21.2, February 2021V0.10.20, January 20183.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++ScalaC and C++
Server operating systemsLinux
Windows
LinuxLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyes 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.nonono
Secondary indexesnonoyes
SQL infoSupport of SQLSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsyes
APIs and other access methodsHTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes, in Luanoyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic, metric affinity per nodeyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter awarenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlnonofine grained access rights according to SQL-standard

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More resources
EventStoreDBIRONdbSpark SQLTransbase
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