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DBMS > Apache IoTDB vs. Drizzle vs. Kinetica vs. SingleStore

System Properties Comparison Apache IoTDB vs. Drizzle vs. Kinetica vs. SingleStore

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDrizzle  Xexclude from comparisonKinetica  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded 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 FlinkMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Fully vectorized database across both GPUs and CPUsMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelTime Series DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score4.02
Rank#74  Overall
#39  Relational DBMS
Websiteiotdb.apache.orgwww.kinetica.comwww.singlestore.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.kinetica.comdocs.singlestore.com
DeveloperApache Software FoundationDrizzle project, originally started by Brian AkerKineticaSingleStore Inc.
Initial release2018200820122013
Current release1.1.0, April 20237.2.4, September 20127.1, August 20218.5, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLcommercialcommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C, C++C++, Go
Server operating systemsAll OS with a Java VM (>= 1.8)FreeBSD
Linux
OS X
LinuxLinux info64 bit version required
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.nonono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageyes infowith proprietary extensionsSQL-like DML and DDL statementsyes infobut no triggers and foreign keys
APIs and other access methodsJDBC
Native API
JDBCJDBC
ODBC
RESTful HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C++
Java
PHP
C++
Java
JavaScript (Node.js)
Python
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnouser defined functionsyes
Triggersyesno infohooks for callbacks inside the server can be used.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)ShardingShardingSharding infohash 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
Source-replica replication
Source-replica replicationSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlyesPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and roles on table levelFine grained access control via users, groups and roles

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More resources
Apache IoTDBDrizzleKineticaSingleStore infoformer name was MemSQL
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