DBMS > Blueflood vs. BoltDB vs. Drizzle vs. Kinetica vs. mSQL

System Properties Comparison Blueflood vs. BoltDB vs. Drizzle vs. Kinetica vs. mSQL

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

Scalable TimeSeries DBMS based on Cassandra

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

Primary database model

Time Series DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	0.09
Rank	#353	Overall
	#33	Time Series DBMS

Score	0.76
Rank	#224	Overall
	#32	Key-value stores

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	1.67
Rank	#151	Overall
	#70	Relational DBMS

Website

blueflood.io

github.com/boltdb/bolt

www.kinetica.com

hughestech.com.au/products/msql

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.kinetica.com

Developer

Rackspace

Drizzle project, originally started by Brian Aker

Kinetica

Hughes Technologies

Initial release

2013

2008

2012

1994

Current release

7.2.4, September 2012

7.1, August 2021

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT License

Open Source

GNU GPL

commercial

free licenses can be provided

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

Java

C++

C, C++

Server operating systems

Linux
OS X

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X

Linux

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

predefined scheme

schema-free

yes

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

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

HTTP REST

JDBC

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

Supported programming languages

C
C++
Java
PHP

C++
Java
JavaScript (Node.js)
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

Server-side scripts

Stored procedures

user defined functions

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Multi-source replication
Source-replica replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

none

Immediate Consistency or Eventual Consistency depending on configuration

none

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

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