DBMS > Drizzle vs. IBM Cloudant vs. Kinetica vs. SWC-DB vs. Tarantool

System Properties Comparison Drizzle vs. IBM Cloudant vs. Kinetica vs. SWC-DB vs. Tarantool

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

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

Database as a Service offering based on Apache CouchDB

Fully vectorized database across both GPUs and CPUs

A high performance, scalable Wide Column DBMS

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

Primary database model

Document store
Key-value store
Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Time Series DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Score	1.67
Rank	#143	Overall
	#25	Document stores
	#25	Key-value stores
	#65	Relational DBMS

Website

www.ibm.com/products/cloudant

www.kinetica.com

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

www.tarantool.io

Technical documentation

cloud.ibm.com/docs/Cloudant

docs.kinetica.com

www.tarantool.io/en/doc

Developer

Drizzle project, originally started by Brian Aker

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Kinetica

Alex Kashirin

Initial release

2008

2010

2012

2020

2008

Current release

7.2.4, September 2012

7.1, August 2021

0.5, April 2021

2.10.0, May 2022

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

GPL V3

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Erlang

C, C++

C++

C and C++

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux

BSD
Linux
macOS

Data scheme

yes

schema-free

yes

schema-free

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

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

SQL-like query language

Full-featured ANSI SQL support

APIs and other access methods

JDBC

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

Proprietary protocol
Thrift

Open binary protocol

Supported programming languages

C
C++
Java
PHP

C#
Java
JavaScript
Objective-C
PHP
Ruby

C++
Java
JavaScript (Node.js)
Python

C++

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

user defined functions

Lua, C and SQL stored procedures

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, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a document possible

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

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

yes, full featured in-memory storage engine with persistence

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users can be defined per database

Access rights for users and roles on table level

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
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9 November 2021, Vladimir Perepelytsya, Tarantool (sponsor)

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