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DBMS > Apache Druid vs. GridGain vs. HBase vs. Kinetica

System Properties Comparison Apache Druid vs. GridGain vs. HBase vs. Kinetica

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGridGain  Xexclude from comparisonHBase  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGridGain is an in-memory computing platform, built on Apache IgniteWide-column store based on Apache Hadoop and on concepts of BigTableFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Wide column storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series 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
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitedruid.apache.orgwww.gridgain.comhbase.apache.orgwww.kinetica.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.gridgain.com/­docs/­index.htmlhbase.apache.org/­book.htmldocs.kinetica.com
DeveloperApache Software Foundation and contributorsGridGain Systems, Inc.Apache Software Foundation infoApache top-level project, originally developed by PowersetKinetica
Initial release2012200720082012
Current release29.0.1, April 2024GridGain 8.5.12.3.4, January 20217.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache version 2commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .NetJavaC, C++
Server operating systemsLinux
OS X
Unix
Linux
OS X
Solaris
Windows
Linux
Unix
Windows infousing Cygwin
Linux
Data schemeyes infoschema-less columns are supportedyesschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes
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 indexesyesyesnoyes
SQL infoSupport of SQLSQL for queryingANSI-99 for query and DML statements, subset of DDLnoSQL-like DML and DDL statements
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)yes infoCoprocessors in Javauser defined functions
Triggersnoyes (cache interceptors and events)yesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes (replicated cache)Multi-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)yesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDSingle row ACID (across millions of columns)no
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.noyesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemSecurity Hooks for custom implementationsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users and roles on table level

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More resources
Apache DruidGridGainHBaseKinetica
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