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DBMS > Apache Druid vs. EsgynDB vs. eXtremeDB vs. GridGain

System Properties Comparison Apache Druid vs. EsgynDB vs. eXtremeDB vs. GridGain

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEsgynDB  Xexclude from comparisoneXtremeDB  Xexclude from comparisonGridGain  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionNatively in-memory DBMS with options for persistency, high-availability and clusteringGridGain is an in-memory computing platform, built on Apache Ignite
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Websitedruid.apache.orgwww.esgyn.cnwww.mcobject.comwww.gridgain.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.mcobject.com/­docs/­extremedb.htmwww.gridgain.com/­docs/­index.html
DeveloperApache Software Foundation and contributorsEsgynMcObjectGridGain Systems, Inc.
Initial release2012201520012007
Current release29.0.1, April 20248.2, 2021GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaC and C++Java, C++, .Net
Server operating systemsLinux
OS X
Unix
LinuxAIX
HP-UX
Linux
macOS
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono infosupport of XML interfaces availableyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingyesyes infowith the option: eXtremeSQLANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
C
C#
C++
Java
Lua
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoJava Stored Proceduresyesyes (compute grid and cache interceptors can be used instead)
Triggersnonoyes infoby defining eventsyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardinghorizontal partitioning / shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication between multi datacentersActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
yes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes (compute grid and hadoop accelerator)
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyes
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 controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardSecurity Hooks for custom implementations
More information provided by the system vendor
Apache DruidEsgynDBeXtremeDBGridGain
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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Apache DruidEsgynDBeXtremeDBGridGain
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