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DBMS > Apache IoTDB vs. Ignite vs. Kinetica vs. Spark SQL

System Properties Comparison Apache IoTDB vs. Ignite vs. Kinetica vs. Spark SQL

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonIgnite  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  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 FlinkApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Fully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteiotdb.apache.orgignite.apache.orgwww.kinetica.comspark.apache.org/­sql
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlapacheignite.readme.io/­docsdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationApache Software FoundationKineticaApache Software Foundation
Initial release2018201520122014
Current release1.1.0, April 2023Apache Ignite 2.67.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialOpen 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 languageJavaC++, Java, .NetC, C++Scala
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Solaris
Windows
LinuxLinux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyesnono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languageANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsJDBC
Native API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyes (compute grid and cache interceptors can be used instead)user defined functionsno
Triggersyesyes (cache interceptors and events)yes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes (replicated cache)Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes (compute grid and hadoop accelerator)no
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 integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlyesSecurity Hooks for custom implementationsAccess rights for users and roles on table levelno

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More resources
Apache IoTDBIgniteKineticaSpark SQL
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