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DBMS > GridGain vs. HugeGraph vs. NSDb vs. STSdb

System Properties Comparison GridGain vs. HugeGraph vs. NSDb vs. STSdb

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonHugeGraph  Xexclude from comparisonNSDb  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteA fast-speed and highly-scalable Graph DBMSScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelKey-value store
Relational DBMS
Graph DBMSTime Series DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitewww.gridgain.comgithub.com/­hugegraph
hugegraph.apache.org
nsdb.iogithub.com/­STSSoft/­STSdb4
Technical documentationwww.gridgain.com/­docs/­index.htmlhugegraph.apache.org/­docsnsdb.io/­Architecture
DeveloperGridGain Systems, Inc.BaiduSTS Soft SC
Initial release2007201820172011
Current releaseGridGain 8.5.10.94.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJavaJava, ScalaC#
Server operating systemsLinux
OS X
Solaris
Windows
Linux
macOS
Unix
Linux
macOS
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringyes infoprimitive types and user defined types (classes)
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.yesnono
Secondary indexesyesyes infoalso supports composite index and range indexall fields are automatically indexedno
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoSQL-like query languageno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP API
TinkerPop Gremlin
gRPC
HTTP REST
WebSocket
.NET Client API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
Groovy
Java
Python
Java
Scala
C#
Java
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)asynchronous Gremlin script jobsnono
Triggersyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes infodepending on used storage backend, e.g. Cassandra and HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)via hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlSecurity Hooks for custom implementationsUsers, roles and permissionsno

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More resources
GridGainHugeGraphNSDbSTSdb
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