DBMS > Drizzle vs. IBM Cloudant vs. Splice Machine vs. TempoIQ

System Properties Comparison Drizzle vs. IBM Cloudant vs. Splice Machine vs. TempoIQ

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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.

TempoIQ seems to be decommissioned. It will be removed 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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

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

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

www.ibm.com/products/cloudant

splicemachine.com

tempoiq.com (offline)

Technical documentation

cloud.ibm.com/docs/Cloudant

splicemachine.com/how-it-works

Developer

Drizzle project, originally started by Brian Aker

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Splice Machine

TempoIQ

Initial release

2008

2010

2014

2012

Current release

7.2.4, September 2012

3.1, March 2021

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

AGPL 3.0, commercial license available

commercial

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

Java

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux
OS X
Solaris
Windows

Data scheme

yes

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

yes

APIs and other access methods

JDBC

RESTful HTTP/JSON API

JDBC
Native Spark Datasource
ODBC

HTTP API

Supported programming languages

C
C++
Java
PHP

C#
Java
JavaScript
Objective-C
PHP
Ruby

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

Java

Triggers

hooks for callbacks inside the server can be used.

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

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

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users can be defined per database

Access rights for users, groups and roles according to SQL-standard

simple authentication-based access control

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More resources

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