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DBMS > Drizzle vs. Firebase Realtime Database vs. IBM Db2 Event Store vs. Kinetica vs. TerarkDB

System Properties Comparison Drizzle vs. Firebase Realtime Database vs. IBM Db2 Event Store vs. Kinetica vs. TerarkDB

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonKinetica  Xexclude from comparisonTerarkDB  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Distributed Event Store optimized for Internet of Things use casesFully vectorized database across both GPUs and CPUsA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelRelational DBMSDocument storeEvent Store
Time Series DBMS
Relational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.29
Rank#39  Overall
#6  Document stores
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitefirebase.google.com/­products/­realtime-databasewww.ibm.com/­products/­db2-event-storewww.kinetica.comgithub.com/­bytedance/­terarkdb
Technical documentationfirebase.google.com/­docs/­databasewww.ibm.com/­docs/­en/­db2-event-storedocs.kinetica.combytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperDrizzle project, originally started by Brian AkerGoogle infoacquired by Google 2014IBMKineticaByteDance, originally Terark
Initial release20082012201720122016
Current release7.2.4, September 20122.07.1, August 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercial infofree developer edition availablecommercialcommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++C, C++C++
Server operating systemsFreeBSD
Linux
OS X
hostedLinux infoLinux, macOS, Windows for the developer additionLinux
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nononono
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLyes infowith proprietary extensionsnoyes infothrough the embedded Spark runtimeSQL-like DML and DDL statementsno
APIs and other access methodsJDBCAndroid
iOS
JavaScript API
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
C++ API
Java API
Supported programming languagesC
C++
Java
PHP
Java
JavaScript
Objective-C
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C++
Java
JavaScript (Node.js)
Python
C++
Java
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'yesuser defined functionsno
Triggersno infohooks for callbacks inside the server can be used.Callbacks are triggered when data changesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Active-active shard replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnonono
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPyes, based on authentication and database rulesfine grained access rights according to SQL-standardAccess rights for users and roles on table levelno

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More resources
DrizzleFirebase Realtime DatabaseIBM Db2 Event StoreKineticaTerarkDB
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