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DBMS > Datomic vs. GridDB vs. Hypertable vs. Microsoft Azure Table Storage

System Properties Comparison Datomic vs. GridDB vs. Hypertable vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGridDB  Xexclude from comparisonHypertable  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionDatomic 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 DataAn open source BigTable implementation based on distributed file systems such as HadoopA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSTime Series DBMSWide column storeWide column store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Websitewww.datomic.comgriddb.netazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationdocs.datomic.comdocs.griddb.net
DeveloperCognitectToshiba CorporationHypertable Inc.Microsoft
Initial release2012201320092012
Current release1.0.7075, December 20235.1, August 20220.9.8.11, March 2016
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGNU version 3. Commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++C++
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Windows infoan inofficial Windows port is available
hosted
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampnoyes
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 indexesyesyesrestricted infoonly exact value or prefix value scansno
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)nono
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
C++ API
Thrift
RESTful HTTP API
Supported programming languagesClojure
Java
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infoTransaction Functionsnonono
TriggersBy using transaction functionsyesnono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replicationselectable replication factor on file system levelyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesno
User concepts infoAccess controlnoAccess rights for users can be defined per databasenoAccess rights based on private key authentication or shared access signatures
More information provided by the system vendor
DatomicGridDBHypertableMicrosoft Azure Table Storage
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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DatomicGridDBHypertableMicrosoft Azure Table Storage
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