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DBMS > Apache Druid vs. BigObject vs. GridGain vs. IBM Db2 Event Store vs. Splice Machine

System Properties Comparison Apache Druid vs. BigObject vs. GridGain vs. IBM Db2 Event Store vs. Splice Machine

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBigObject  Xexclude from comparisonGridGain  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic DBMS for real-time computations and queriesGridGain is an in-memory computing platform, built on Apache IgniteDistributed Event Store optimized for Internet of Things use casesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMS infoa hierachical model (tree) can be imposedKey-value store
Relational DBMS
Event Store
Time Series DBMS
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
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitedruid.apache.orgbigobject.iowww.gridgain.comwww.ibm.com/­products/­db2-event-storesplicemachine.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.bigobject.iowww.gridgain.com/­docs/­index.htmlwww.ibm.com/­docs/­en/­db2-event-storesplicemachine.com/­how-it-works
DeveloperApache Software Foundation and contributorsBigObject, Inc.GridGain Systems, Inc.IBMSplice Machine
Initial release20122015200720172014
Current release29.0.1, April 2024GridGain 8.5.12.03.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree community edition availablecommercialcommercial infofree developer edition availableOpen Source infoAGPL 3.0, commercial license available
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 languageJavaJava, C++, .NetC and C++Java
Server operating systemsLinux
OS X
Unix
Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
OS X
Solaris
Windows
Linux infoLinux, macOS, Windows for the developer additionLinux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesyesyesyes
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.nonoyesno
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLyes infothrough the embedded Spark runtimeyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
fluentd
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoLuayes (compute grid and cache interceptors can be used instead)yesyes infoJava
Triggersnonoyes (cache interceptors and events)noyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednoneShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnoneyes (replicated cache)Active-active shard replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes (compute grid and hadoop accelerator)noYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesNo - written data is immutableyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache DruidBigObjectGridGainIBM Db2 Event StoreSplice Machine
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