DBMS > BoltDB vs. Drizzle vs. Kinetica vs. Linter vs. SWC-DB

System Properties Comparison BoltDB vs. Drizzle vs. Kinetica vs. Linter vs. SWC-DB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

An embedded key-value store for Go.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Fully vectorized database across both GPUs and CPUs

RDBMS for high security requirements

A high performance, scalable Wide Column DBMS

Primary database model

Key-value store

Relational DBMS

Wide column store

Secondary database models

Spatial DBMS
Time Series DBMS

Spatial DBMS

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

github.com/boltdb/bolt

www.kinetica.com

linter.ru

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.kinetica.com

Developer

Drizzle project, originally started by Brian Aker

Kinetica

relex.ru

Alex Kashirin

Initial release

2013

2008

2012

1990

2020

Current release

7.2.4, September 2012

7.1, August 2021

0.5, April 2021

License

Commercial or Open Source

Open Source

MIT License

Open Source

GNU GPL

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C, C++

C and C++

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X

Linux

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements

yes

SQL-like query language

APIs and other access methods

JDBC

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Proprietary protocol
Thrift

Supported programming languages

C
C++
Java
PHP

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C++

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

hooks for callbacks inside the server can be used.

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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