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DBMS > Apache IoTDB vs. Datomic vs. GridDB vs. Manticore Search

System Properties Comparison Apache IoTDB vs. Datomic vs. GridDB vs. Manticore Search

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDatomic  Xexclude from comparisonGridDB  Xexclude from comparisonManticore Search  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 FlinkDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityScalable in-memory time series database optimized for IoT and Big DataMulti-storage database for search, including full-text search.
Primary database modelTime Series DBMSRelational DBMSTime Series DBMSSearch engine
Secondary database modelsKey-value store
Relational DBMS
Time Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.29
Rank#302  Overall
#21  Search engines
Websiteiotdb.apache.orgwww.datomic.comgriddb.netmanticoresearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.datomic.comdocs.griddb.netmanual.manticoresearch.com
DeveloperApache Software FoundationCognitectToshiba CorporationManticore Software
Initial release2018201220132017
Current release1.1.0, April 20231.0.7075, December 20235.1, August 20226.0, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infolimited edition freeOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGPL version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, ClojureC++C++
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VMLinuxFreeBSD
Linux
macOS
Windows
Data schemeyesyesyesFixed schema
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean
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.nononoCan index from XML
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languagenoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language
APIs and other access methodsJDBC
Native API
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Clojure
Java
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresyesyes infoTransaction Functionsnouser defined functions
TriggersyesBy using transaction functionsyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)none infoBut extensive use of caching in the application peersShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnone infoBut extensive use of caching in the application peersSource-replica replicationSynchronous replication based on Galera library
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container levelyes infoisolated transactions for atomic changes and binary logging for safe writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes infoThe original contents of fields are not stored in the Manticore index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentyes
User concepts infoAccess controlyesnoAccess rights for users can be defined per databaseno
More information provided by the system vendor
Apache IoTDBDatomicGridDBManticore Search
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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Apache IoTDBDatomicGridDBManticore Search
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