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DBMS > BoltDB vs. Drizzle vs. Google Cloud Bigtable vs. Kinetica vs. Linter

System Properties Comparison BoltDB vs. Drizzle vs. Google Cloud Bigtable vs. Kinetica vs. Linter

Editorial information provided by DB-Engines
NameBoltDB  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKinetica  Xexclude from comparisonLinter  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.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully vectorized database across both GPUs and CPUsRDBMS for high security requirements
Primary database modelKey-value storeRelational DBMSKey-value store
Wide column store
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.74
Rank#220  Overall
#31  Key-value stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Websitegithub.com/­boltdb/­boltcloud.google.com/­bigtablewww.kinetica.comlinter.ru
Technical documentationcloud.google.com/­bigtable/­docsdocs.kinetica.com
DeveloperDrizzle project, originally started by Brian AkerGoogleKineticarelex.ru
Initial release20132008201520121990
Current release7.2.4, September 20127.1, August 2021
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoGNU GPLcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++C, C++C and C++
Server operating systemsBSD
Linux
OS X
Solaris
Windows
FreeBSD
Linux
OS X
hostedLinuxAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or datenoyesnoyesyes
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 indexesnoyesnoyesyes
SQL infoSupport of SQLnoyes infowith proprietary extensionsnoSQL-like DML and DDL statementsyes
APIs and other access methodsJDBCgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languagesGoC
C++
Java
PHP
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresnononouser defined functionsyes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersnono infohooks for callbacks inside the server can be used.noyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Internal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDAtomic single-row operationsnoACID
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 RAM
User concepts infoAccess controlnoPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
BoltDBDrizzleGoogle Cloud BigtableKineticaLinter
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