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DBMS > BoltDB vs. Drizzle vs. Kinetica vs. Microsoft Azure Data Explorer vs. OmniSci

System Properties Comparison BoltDB vs. Drizzle vs. Kinetica vs. Microsoft Azure Data Explorer vs. OmniSci

Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonDrizzle  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018  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.
DescriptionAn embedded key-value store for Go.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.GPU-accelerated database for real-time analysis of large and streaming datasetsFully managed big data interactive analytics platformA high performance, in-memory, column-oriented RDBMS, designed to run on GPUs
Primary database modelKey-value storeRelational DBMSRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#193  Overall
#32  Key-value stores
Score0.53
Rank#199  Overall
#97  Relational DBMS
Score1.65
Rank#118  Overall
#61  Relational DBMS
Score2.08
Rank#105  Overall
#52  Relational DBMS
Websitegithub.com/­boltdb/­boltwww.kinetica.comazure.microsoft.com/­services/­data-explorerwww.omnisci.com
Technical documentationwww.kinetica.com/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.omnisci.com/­docs/­latest
DeveloperDrizzle project, originally started by Brian AkerKineticaMicrosoftMapD Technologies, Inc.
Initial release20132008201220192016
Current release7.2.4, September 20126.0V4
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoGNU GPLcommercialcommercialOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++C, C++C++ and CUDA
Server operating systemsBSD
Linux
OS X
Solaris
Windows
FreeBSD
Linux
OS X
LinuxhostedLinux
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or datenoyesyesyesyes
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 indexesnoyesyesno
SQL infoSupport of SQLnoyes infowith proprietary extensionsSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJDBCRESTful HTTP API
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Thrift
JDBC
ODBC
Supported programming languagesGoC
C++
Java
PHP
C++
Java
JavaScript (Node.js)
Python
.Net
Java
JavaScript (Node.js)
PowerShell
Python
R
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresnonouser defined functionsYes. Languages: KQL, Python, Rno
Triggersnono infohooks for callbacks inside the server can be used.yes infotriggers when inserted values for one or more columns fall within a specified rangeTable-level update policy rules can be used to automatically run a query and ingest its results when data is ingested into another table.no
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoImplicit feature of the cloud serviceSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMaster-master replication
Master-slave replication
Master-slave replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Master-master replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnonono
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.noyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlnoPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and roles on table levelAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
BoltDBDrizzleKineticaMicrosoft Azure Data ExplorerOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018
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