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DBMS > Apache IoTDB vs. EsgynDB vs. JaguarDB vs. Spark SQL vs. Splice Machine

System Properties Comparison Apache IoTDB vs. EsgynDB vs. JaguarDB vs. Spark SQL vs. Splice Machine

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonJaguarDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionPerformant, highly scalable DBMS for AI and IoT applicationsSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSRelational DBMSKey-value store
Vector DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.06
Rank#381  Overall
#59  Key-value stores
#13  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteiotdb.apache.orgwww.esgyn.cnwww.jaguardb.comspark.apache.org/­sqlsplicemachine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.jaguardb.com/­support.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperApache Software FoundationEsgynDataJaguar, Inc.Apache Software FoundationSplice Machine
Initial release20182015201520142014
Current release1.1.0, April 20233.3 July 20233.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGPL V3.0Open Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaC++ infothe server part. Clients available in other languagesScalaJava
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinuxLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like query languageyesA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
JDBC
ODBC
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages supporting JDBC/ODBC/ADO.NetC
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesJava Stored Proceduresnonoyes infoJava
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication between multi datacentersMulti-source replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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.yesnononoyes
User concepts infoAccess controlyesfine grained access rights according to SQL-standardrights management via user accountsnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache IoTDBEsgynDBJaguarDBSpark SQLSplice Machine
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