DBMS > Cachelot.io vs. FatDB vs. Quasardb vs. Splice Machine

System Properties Comparison Cachelot.io vs. FatDB vs. Quasardb vs. Splice Machine

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

In-memory caching system

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Distributed, high-performance timeseries database

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

Primary database model

Key-value store

Document store
Key-value store

Time Series DBMS

Relational DBMS

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

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

cachelot.io

quasar.ai

splicemachine.com

Technical documentation

doc.quasar.ai/master

splicemachine.com/how-it-works

Developer

FatCloud

quasardb

Splice Machine

Initial release

2015

2012

2009

2014

Current release

3.14.1, January 2024

3.1, March 2021

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

AGPL 3.0, commercial license available

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++

Java

Server operating systems

FreeBSD
Linux
OS X

Windows

BSD
Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

Via inetgration in SQL Server

SQL-like query language

yes

APIs and other access methods

Memcached protocol

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

HTTP API

JDBC
Native Spark Datasource
ODBC

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

Server-side scripts

Stored procedures

yes

via applications

yes

Java

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

consistent hashing

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Source-replica replication with selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

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

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

User concepts

Access control

Can implement custom security layer via applications

Cryptographically strong user authentication and audit trail

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

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