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DBMS > Brytlyt vs. Datomic vs. GridDB vs. Hypertable

System Properties Comparison Brytlyt vs. Datomic vs. GridDB vs. Hypertable

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Editorial information provided by DB-Engines
NameBrytlyt  Xexclude from comparisonDatomic  Xexclude from comparisonGridDB  Xexclude from comparisonHypertable  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLDatomic 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 Hadoop
Primary database modelRelational DBMSRelational DBMSTime Series DBMSWide column store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websitebrytlyt.iowww.datomic.comgriddb.net
Technical documentationdocs.brytlyt.iodocs.datomic.comdocs.griddb.net
DeveloperBrytlytCognitectToshiba CorporationHypertable Inc.
Initial release2016201220132009
Current release5.0, August 20231.0.6735, June 20235.1, August 20220.9.8.11, March 2016
License infoCommercial or Open Sourcecommercialcommercial 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 available
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 languageC, C++ and CUDAJava, ClojureC++C++
Server operating systemsLinux
OS X
Windows
All OS with a Java VMLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampno
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.yes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesyesrestricted infoonly exact value or prefix value scans
SQL infoSupport of SQLyesnoSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
C++ API
Thrift
Supported programming languages.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Clojure
Java
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin PL/pgSQLyes infoTransaction Functionsnono
TriggersyesBy using transaction functionsyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone infoBut extensive use of caching in the application peersSource-replica replicationselectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at container levelno
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
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 developmentyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users can be defined per databaseno
More information provided by the system vendor
BrytlytDatomicGridDBHypertable
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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BrytlytDatomicGridDBHypertable
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