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DBMS > EsgynDB vs. GridGain vs. Hive vs. HugeGraph vs. Vitess

System Properties Comparison EsgynDB vs. GridGain vs. Hive vs. HugeGraph vs. Vitess

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGridGain  Xexclude from comparisonHive  Xexclude from comparisonHugeGraph  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGridGain is an in-memory computing platform, built on Apache Ignitedata warehouse software for querying and managing large distributed datasets, built on HadoopA fast-speed and highly-scalable Graph DBMSScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSGraph DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.esgyn.cnwww.gridgain.comhive.apache.orggithub.com/­hugegraph
hugegraph.apache.org
vitess.io
Technical documentationwww.gridgain.com/­docs/­index.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homehugegraph.apache.org/­docsvitess.io/­docs
DeveloperEsgynGridGain Systems, Inc.Apache Software Foundation infoinitially developed by FacebookBaiduThe Linux Foundation, PlanetScale
Initial release20152007201220182013
Current releaseGridGain 8.5.13.1.3, April 20220.915.0.2, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJava, C++, .NetJavaJavaGo
Server operating systemsLinuxLinux
OS X
Solaris
Windows
All OS with a Java VMLinux
macOS
Unix
Docker
Linux
macOS
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.noyesno
Secondary indexesyesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsnoyes infowith proprietary extensions
APIs and other access methodsADO.NET
JDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
Java API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
PHP
Python
Groovy
Java
Python
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresJava Stored Proceduresyes (compute grid and cache interceptors can be used instead)yes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobsyes infoproprietary syntax
Triggersnoyes (cache interceptors and events)nonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes (replicated cache)selectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBaseMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)yes infoquery execution via MapReducevia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integrityyesnonoyes infoedges in graphyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsAccess rights for users, groups and rolesUsers, roles and permissionsUsers with fine-grained authorization concept infono user groups or roles

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More resources
EsgynDBGridGainHiveHugeGraphVitess
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