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DBMS > Apache IoTDB vs. GridGain vs. KeyDB vs. TimescaleDB

System Properties Comparison Apache IoTDB vs. GridGain vs. KeyDB vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGridGain  Xexclude from comparisonKeyDB  Xexclude from comparisonTimescaleDB  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 FlinkGridGain is an in-memory computing platform, built on Apache IgniteAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Key-value storeTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.70
Rank#229  Overall
#32  Key-value stores
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websiteiotdb.apache.orgwww.gridgain.comgithub.com/­Snapchat/­KeyDB
keydb.dev
www.timescale.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.gridgain.com/­docs/­index.htmldocs.keydb.devdocs.timescale.com
DeveloperApache Software FoundationGridGain Systems, Inc.EQ Alpha Technology Ltd.Timescale
Initial release2018200720192017
Current release1.1.0, April 2023GridGain 8.5.12.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoBSD-3Open 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 languageJavaJava, C++, .NetC++C
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Solaris
Windows
LinuxLinux
OS X
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.noyesnoyes
Secondary indexesyesyesyes infoby using the Redis Search moduleyes
SQL infoSupport of SQLSQL-like query languageANSI-99 for query and DML statements, subset of DDLnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
Native API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocol infoRESP - REdis Serialization ProtocoADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesyes (compute grid and cache interceptors can be used instead)Luauser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyes (cache interceptors and events)noyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingShardingyes, across time and space (hash partitioning) attributes
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)Multi-source replication
Source-replica replication
Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDOptimistic locking, atomic execution of commands blocks and scriptsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlyesSecurity Hooks for custom implementationssimple password-based access control and ACLfine grained access rights according to SQL-standard

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More resources
Apache IoTDBGridGainKeyDBTimescaleDB
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