DBMS > KairosDB vs. Sadas Engine vs. Splice Machine vs. SQL.JS

System Properties Comparison KairosDB vs. Sadas Engine vs. Splice Machine vs. SQL.JS

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Editorial information provided by DB-Engines

Name

Description

Distributed Time Series DBMS based on Cassandra or H2

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

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

Port of SQLite to JavaScript

Primary database model

Time Series DBMS

Relational DBMS

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

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.53
Rank	#252	Overall
	#116	Relational DBMS

Website

github.com/kairosdb/kairosdb

www.sadasengine.com

splicemachine.com

sql.js.org

Technical documentation

kairosdb.github.io

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

splicemachine.com/how-it-works

sql.js.org/documentation/index.html

Developer

SADAS s.r.l.

Splice Machine

Alon Zakai

enhancements implemented by others

Initial release

2013

2006

2014

2012

Current release

1.2.2, November 2018

8.0

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free trial version available

Open Source

AGPL 3.0, commercial license available

Open Source

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++

Java

JavaScript

Server operating systems

Linux
OS X
Windows

AIX
Linux
Windows

Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data 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

SQL-92 is not fully supported

APIs and other access methods

Graphite protocol
HTTP REST
Telnet API

JDBC
ODBC
Proprietary protocol

JDBC
Native Spark Datasource
ODBC

JavaScript API

Supported programming languages

Java
JavaScript

Node.js
PHP
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

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

JavaScript

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

except by serializing a db to a file

In-memory capabilities

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

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

simple password-based access control

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

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More resources

DB-Engines blog posts

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1 December 2014, Matthias Gelbmann

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