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DBMS > GridDB vs. Hive vs. RavenDB vs. Speedb

System Properties Comparison GridDB vs. Hive vs. RavenDB vs. Speedb

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHive  Xexclude from comparisonRavenDB  Xexclude from comparisonSpeedb  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big Datadata warehouse software for querying and managing large distributed datasets, built on HadoopOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseAn embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDB
Primary database modelTime Series DBMSRelational DBMSDocument storeKey-value store
Secondary database modelsKey-value store
Relational DBMS
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Score0.26
Rank#310  Overall
#45  Key-value stores
Websitegriddb.nethive.apache.orgravendb.netwww.speedb.io
Technical documentationdocs.griddb.netcwiki.apache.org/­confluence/­display/­Hive/­Homeravendb.net/­docs
DeveloperToshiba CorporationApache Software Foundation infoinitially developed by FacebookHibernating RhinosSpeedb
Initial release2013201220102020
Current release5.1, August 20223.1.3, April 20225.4, July 2022
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2Open Source infoAGPL version 3, commercial license availableOpen Source infoApache Version 2.0; 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++JavaC#C++
Server operating systemsLinuxAll OS with a Java VMLinux
macOS
Raspberry Pi
Windows
Linux
Windows
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesnono
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.nono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statementsSQL-like query language (RQL)no
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
PHP
Python
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyesno
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factorMulti-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoACID, Cluster-wide transaction availableyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users, groups and rolesAuthorization levels configured per client per databaseno
More information provided by the system vendor
GridDBHiveRavenDBSpeedb
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Speedb is an embedded key-value storage engine for versatile use cases. It was designed...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Speedb Open-source rebases on RocksDB's latest versions, with enhanced capabilities...
» 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
Open source - Speedb OSS is released under an Apache license and can be found on...
» more

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GridDBHiveRavenDBSpeedb
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