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DBMS > Apache Druid vs. BigchainDB vs. Dragonfly vs. GridGain vs. IBM Db2 Event Store

System Properties Comparison Apache Druid vs. BigchainDB vs. Dragonfly vs. GridGain vs. IBM Db2 Event Store

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonBigchainDB  Xexclude from comparisonDragonfly  Xexclude from comparisonGridGain  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataBigchainDB is scalable blockchain database offering decentralization, immutability and native assetsA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceGridGain is an in-memory computing platform, built on Apache IgniteDistributed Event Store optimized for Internet of Things use cases
Primary database modelRelational DBMS
Time Series DBMS
Document storeKey-value storeKey-value store
Relational DBMS
Event Store
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
Score0.79
Rank#212  Overall
#36  Document stores
Score0.41
Rank#266  Overall
#38  Key-value stores
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Websitedruid.apache.orgwww.bigchaindb.comgithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.gridgain.comwww.ibm.com/­products/­db2-event-store
Technical documentationdruid.apache.org/­docs/­latest/­designbigchaindb.readthedocs.io/­en/­latestwww.dragonflydb.io/­docswww.gridgain.com/­docs/­index.htmlwww.ibm.com/­docs/­en/­db2-event-store
DeveloperApache Software Foundation and contributorsDragonflyDB team and community contributorsGridGain Systems, Inc.IBM
Initial release20122016202320072017
Current release29.0.1, April 20241.0, March 2023GridGain 8.5.12.0
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoAGPL v3Open Source infoBSL 1.1commercialcommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaPythonC++Java, C++, .NetC and C++
Server operating systemsLinux
OS X
Unix
LinuxLinuxLinux
OS X
Solaris
Windows
Linux infoLinux, macOS, Windows for the developer addition
Data schemeyes infoschema-less columns are supportedschema-freescheme-freeyesyes
Typing infopredefined data types such as float or dateyesnostrings, hashes, lists, sets, sorted sets, bit arraysyesyes
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.nononoyesno
Secondary indexesyesnoyesno
SQL infoSupport of SQLSQL for queryingnonoANSI-99 for query and DML statements, subset of DDLyes infothrough the embedded Spark runtime
APIs and other access methodsJDBC
RESTful HTTP/JSON API
CLI Client
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization ProtocolHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Haskell
Java
JavaScript
Python
Ruby
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
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
Server-side scripts infoStored proceduresnoLuayes (compute grid and cache interceptors can be used instead)yes
Triggersnopublish/subscribe channels provide some trigger functionalityyes (cache interceptors and events)no
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 enginesselectable replication factorSource-replica replicationyes (replicated cache)Active-active shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of command blocks and scriptsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, strict serializability by the serveryesNo - written data is immutable
Durability infoSupport for making data persistentyesyes,with MongoDB ord RethinkDByesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesPassword-based authenticationSecurity Hooks for custom implementationsfine grained access rights according to SQL-standard

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More resources
Apache DruidBigchainDBDragonflyGridGainIBM Db2 Event Store
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