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DBMS > GridDB vs. JanusGraph vs. Manticore Search vs. RocksDB

System Properties Comparison GridDB vs. JanusGraph vs. Manticore Search vs. RocksDB

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonManticore Search  Xexclude from comparisonRocksDB  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Multi-storage database for search, including full-text search.Embeddable persistent key-value store optimized for fast storage (flash and RAM)
Primary database modelTime Series DBMSGraph DBMSSearch engineKey-value store
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
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score0.22
Rank#312  Overall
#21  Search engines
Score3.65
Rank#85  Overall
#11  Key-value stores
Websitegriddb.netjanusgraph.orgmanticoresearch.comrocksdb.org
Technical documentationdocs.griddb.netdocs.janusgraph.orgmanual.manticoresearch.comgithub.com/­facebook/­rocksdb/­wiki
DeveloperToshiba CorporationLinux Foundation; originally developed as Titan by AureliusManticore SoftwareFacebook, Inc.
Initial release2013201720172013
Current release5.1, August 20220.6.3, February 20236.0, February 20238.11.4, April 2024
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 2.0Open Source infoGPL version 2Open Source infoBSD
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++C++
Server operating systemsLinuxLinux
OS X
Unix
Windows
FreeBSD
Linux
macOS
Windows
Linux
Data schemeyesyesFixed schemaschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanno
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.nonoCan index from XMLno
Secondary indexesyesyesyes infofull-text index on all search fieldsno
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noSQL-like query languageno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
C++ API
Java API
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Clojure
Java
Python
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresnoyesuser defined functionsno
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesSynchronous replication based on Galera libraryyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes infovia Faunus, a graph analytics enginenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDyes infoisolated transactions for atomic changes and binary logging for safe writesyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes infoThe original contents of fields are not stored in the Manticore index.yes
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 databaseUser authentification and security via Rexster Graph Servernono
More information provided by the system vendor
GridDBJanusGraph infosuccessor of TitanManticore SearchRocksDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
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Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
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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)
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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3rd partiesSpeedb: A high performance RocksDB-compliant key-value store optimized for write-intensive workloads.
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More resources
GridDBJanusGraph infosuccessor of TitanManticore SearchRocksDB
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