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DBMS > EsgynDB vs. GridGain vs. Hive vs. HugeGraph vs. Teradata Aster

System Properties Comparison EsgynDB vs. GridGain vs. Hive vs. HugeGraph vs. Teradata Aster

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGridGain  Xexclude from comparisonHive  Xexclude from comparisonHugeGraph  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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 DBMSPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSGraph DBMSRelational 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
Websitewww.esgyn.cnwww.gridgain.comhive.apache.orggithub.com/­hugegraph
hugegraph.apache.org
Technical documentationwww.gridgain.com/­docs/­index.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homehugegraph.apache.org/­docs
DeveloperEsgynGridGain Systems, Inc.Apache Software Foundation infoinitially developed by FacebookBaiduTeradata
Initial release20152007201220182005
Current releaseGridGain 8.5.13.1.3, April 20220.9
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0commercial
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++, .NetJavaJava
Server operating systemsLinuxLinux
OS X
Solaris
Windows
All OS with a Java VMLinux
macOS
Unix
Linux
Data schemeyesyesyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
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.noyesnoyes infoin Aster File Store
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
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
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
PHP
Python
Groovy
Java
Python
C
C#
C++
Java
Python
R
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 jobsR packages
Triggersnoyes (cache interceptors and events)nonono
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 HBaseyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes (compute grid and hadoop accelerator)yes infoquery execution via MapReducevia hugegraph-sparkyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDACID
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.noyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsAccess rights for users, groups and rolesUsers, roles and permissionsfine grained access rights according to SQL-standard

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More resources
EsgynDBGridGainHiveHugeGraphTeradata Aster
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