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

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

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGridGain  Xexclude from comparisonHBase  Xexclude from comparisonHive  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGridGain is an in-memory computing platform, built on Apache IgniteWide-column store based on Apache Hadoop and on concepts of BigTabledata warehouse software for querying and managing large distributed datasets, built on HadoopA fast-speed and highly-scalable Graph DBMS
Primary database modelRelational DBMSKey-value store
Relational DBMS
Wide column storeRelational DBMSGraph 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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websitewww.esgyn.cnwww.gridgain.comhbase.apache.orghive.apache.orggithub.com/­hugegraph
hugegraph.apache.org
Technical documentationwww.gridgain.com/­docs/­index.htmlhbase.apache.org/­book.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homehugegraph.apache.org/­docs
DeveloperEsgynGridGain Systems, Inc.Apache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by FacebookBaidu
Initial release20152007200820122018
Current releaseGridGain 8.5.12.3.4, January 20213.1.3, April 20220.9
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2Open Source infoApache Version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJava, C++, .NetJavaJavaJava
Server operating systemsLinuxLinux
OS X
Solaris
Windows
Linux
Unix
Windows infousing Cygwin
All OS with a Java VMLinux
macOS
Unix
Data schemeyesyesschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyesyes
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.noyesnono
Secondary indexesyesyesnoyesyes infoalso supports composite index and range index
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLnoSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
Java API
RESTful HTTP API
TinkerPop Gremlin
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
Groovy
Java
Python
Server-side scripts infoStored proceduresJava Stored Proceduresyes (compute grid and cache interceptors can be used instead)yes infoCoprocessors in Javayes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobs
Triggersnoyes (cache interceptors and events)yesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes (replicated cache)Multi-source replication
Source-replica replication
selectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)yesyes infoquery execution via MapReducevia hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnononoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDSingle row ACID (across millions of columns)noACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and rolesUsers, roles and permissions

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More resources
EsgynDBGridGainHBaseHiveHugeGraph
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