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DBMS > Drizzle vs. Google Cloud Bigtable vs. JaguarDB vs. Kinetica vs. Microsoft Azure Table Storage

System Properties Comparison Drizzle vs. Google Cloud Bigtable vs. JaguarDB vs. Kinetica vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonJaguarDB  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Table Storage  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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Performant, highly scalable DBMS for AI and IoT applicationsFully vectorized database across both GPUs and CPUsA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value store
Vector DBMS
Relational DBMSWide column store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Websitecloud.google.com/­bigtablewww.jaguardb.comwww.kinetica.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationcloud.google.com/­bigtable/­docswww.jaguardb.com/­support.htmldocs.kinetica.com
DeveloperDrizzle project, originally started by Brian AkerGoogleDataJaguar, Inc.KineticaMicrosoft
Initial release20082015201520122012
Current release7.2.4, September 20123.3 July 20237.1, August 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoGPL V3.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++ infothe server part. Clients available in other languagesC, C++
Server operating systemsFreeBSD
Linux
OS X
hostedLinuxLinuxhosted
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyesyes
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 indexesyesnoyesyesno
SQL infoSupport of SQLyes infowith proprietary extensionsnoA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersSQL-like DML and DDL statementsno
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesC
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresnononouser defined functionsno
Triggersno infohooks for callbacks inside the server can be used.nonoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replicationSource-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnonooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)rights management via user accountsAccess rights for users and roles on table levelAccess rights based on private key authentication or shared access signatures

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More resources
DrizzleGoogle Cloud BigtableJaguarDBKineticaMicrosoft Azure Table Storage
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