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DBMS > Badger vs. EsgynDB vs. GridGain vs. HugeGraph

System Properties Comparison Badger vs. EsgynDB vs. GridGain vs. HugeGraph

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonEsgynDB  Xexclude from comparisonGridGain  Xexclude from comparisonHugeGraph  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGridGain is an in-memory computing platform, built on Apache IgniteA fast-speed and highly-scalable Graph DBMS
Primary database modelKey-value storeRelational DBMSKey-value store
Relational DBMS
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Websitegithub.com/­dgraph-io/­badgerwww.esgyn.cnwww.gridgain.comgithub.com/­hugegraph
hugegraph.apache.org
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerwww.gridgain.com/­docs/­index.htmlhugegraph.apache.org/­docs
DeveloperDGraph LabsEsgynGridGain Systems, Inc.Baidu
Initial release2017201520072018
Current releaseGridGain 8.5.10.9
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++, JavaJava, C++, .NetJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
LinuxLinux
OS X
Solaris
Windows
Linux
macOS
Unix
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nonoyesno
Secondary indexesnoyesyesyes infoalso supports composite index and range index
SQL infoSupport of SQLnoyesANSI-99 for query and DML statements, subset of DDLno
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
TinkerPop Gremlin
Supported programming languagesGoAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Java
PHP
Python
Ruby
Scala
Groovy
Java
Python
Server-side scripts infoStored proceduresnoJava Stored Proceduresyes (compute grid and cache interceptors can be used instead)asynchronous Gremlin script jobs
Triggersnonoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBase
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication between multi datacentersyes (replicated cache)yes infodepending on used storage backend, e.g. Cassandra and HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes (compute grid and hadoop accelerator)via hugegraph-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnoyes infoedges in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardSecurity Hooks for custom implementationsUsers, roles and permissions

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More resources
BadgerEsgynDBGridGainHugeGraph
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