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DBMS > Apache IoTDB vs. EJDB vs. Spark SQL vs. Tigris vs. Transbase

System Properties Comparison Apache IoTDB vs. EJDB vs. Spark SQL vs. Tigris vs. Transbase

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEJDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigris  Xexclude from comparisonTransbase  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 FlinkEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Spark SQL is a component on top of 'Spark Core' for structured data processingA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructureA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelTime Series DBMSDocument storeRelational DBMSDocument store
Key-value store
Search engine
Time Series DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.31
Rank#296  Overall
#44  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.09
Rank#363  Overall
#49  Document stores
#54  Key-value stores
#22  Search engines
#38  Time Series DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websiteiotdb.apache.orggithub.com/­Softmotions/­ejdbspark.apache.org/­sqlwww.tigrisdata.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tigrisdata.com/­docswww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software FoundationSoftmotionsApache Software FoundationTigris Data, Inc.Transaction Software GmbH
Initial release20182012201420221987
Current release1.1.0, April 20233.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGPLv2Open Source infoApache 2.0Open Source infoApache Version 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 languageJavaCScalaC and C++
Server operating systemsAll OS with a Java VM (>= 1.8)server-lessLinux
OS X
Windows
Linux
macOS
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyesyesyes
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 indexesyesnonoyesyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
Native API
in-process shared libraryJDBC
ODBC
CLI Client
gRPC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
Java
Python
R
Scala
Go
Java
JavaScript (Node.js)
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyesnononoyes
Triggersyesnononoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnonenoneyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possiblenoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDyes
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using FoundationDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlyesnonoAccess rights for users and rolesfine grained access rights according to SQL-standard

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More resources
Apache IoTDBEJDBSpark SQLTigrisTransbase
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