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DBMS > Apache IoTDB vs. EXASOL vs. Spark SQL vs. STSdb vs. Teradata Aster

System Properties Comparison Apache IoTDB vs. EXASOL vs. Spark SQL vs. STSdb vs. Teradata Aster

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonEXASOL  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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 FlinkHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Spark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodPlatform for big data analytics on multistructured data sources and types
Primary database modelTime Series DBMSRelational DBMSRelational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websiteiotdb.apache.orgwww.exasol.comspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.exasol.com/­resourcesspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationExasolApache Software FoundationSTS Soft SCTeradata
Initial release20182000201420112005
Current release1.1.0, April 20233.5.0 ( 2.13), September 20234.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoGPLv2, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC#
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
WindowsLinux
Data schemeyesyesyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesyes infoprimitive types and user defined types (classes)yes
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.nononoyes infoin Aster File Store
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLSQL-like query languageyesSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
Native API
.Net
JDBC
ODBC
WebSocket
JDBC
ODBC
.NET Client APIADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Java
Lua
Python
R
Java
Python
R
Scala
C#
Java
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyesuser defined functionsnonoR packages
Triggersyesyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardingyes, utilizing Spark CorenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnonenoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes infoHadoop integrationnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
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.yesyesnono
User concepts infoAccess controlyesAccess rights for users, groups and roles according to SQL-standardnonofine grained access rights according to SQL-standard

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More resources
Apache IoTDBEXASOLSpark SQLSTSdbTeradata Aster
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