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DBMS > EventStoreDB vs. GBase vs. LeanXcale vs. Spark SQL

System Properties Comparison EventStoreDB vs. GBase vs. LeanXcale vs. Spark SQL

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Editorial information provided by DB-Engines
NameEventStoreDB  Xexclude from comparisonGBase  Xexclude from comparisonLeanXcale  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionIndustrial-strength, open-source database solution built from the ground up for event sourcing.Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelEvent StoreRelational DBMSKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.10
Rank#179  Overall
#1  Event Stores
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score0.29
Rank#291  Overall
#41  Key-value stores
#132  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.eventstore.comwww.gbase.cnwww.leanxcale.comspark.apache.org/­sql
Technical documentationdevelopers.eventstore.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEvent Store LimitedGeneral Data Technology Co., Ltd.LeanXcaleApache Software Foundation
Initial release2012200420152014
Current release21.2, February 2021GBase 8a, GBase 8s, GBase 8c3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen SourcecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, PythonScala
Server operating systemsLinux
Windows
LinuxLinux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes
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.yesno
Secondary indexesyesno
SQL infoSupport of SQLStandard with numerous extensionsyes infothrough Apache DerbySQL-like DML and DDL statements
APIs and other access methodsADO.NET
C API
JDBC
ODBC
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
JDBC
ODBC
Supported programming languagesC#C
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsno
Triggersyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range, list and hash) and vertical partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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.yesno
User concepts infoAccess controlyesno

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More resources
EventStoreDBGBaseLeanXcaleSpark SQL
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