DBMS > Datastax Enterprise vs. FatDB vs. JaguarDB vs. Splice Machine vs. STSdb

System Properties Comparison Datastax Enterprise vs. FatDB vs. JaguarDB vs. Splice Machine vs. STSdb

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

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

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

Performant, highly scalable DBMS for AI and IoT applications

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Wide column store

Document store
Key-value store

Key-value store
Vector DBMS

Relational DBMS

Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	6.31
Rank	#57	Overall
	#4	Wide column stores

Score	0.09
Rank	#356	Overall
	#53	Key-value stores
	#13	Vector DBMS

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Score	0.06
Rank	#365	Overall
	#55	Key-value stores

Website

www.datastax.com/products/datastax-enterprise

www.jaguardb.com

splicemachine.com

github.com/STSSoft/STSdb4

Technical documentation

docs.datastax.com

www.jaguardb.com/support.html

splicemachine.com/how-it-works

Developer

DataStax

FatCloud

DataJaguar, Inc.

Splice Machine

STS Soft SC

Initial release

2011

2012

2015

2014

2011

Current release

6.8, April 2020

3.3 July 2023

3.1, March 2021

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

Open Source

AGPL 3.0, commercial license available

Open Source

GPLv2, 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.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

Implementation language

Java

C++

the server part. Clients available in other languages

Java

Server operating systems

Linux
OS X

Windows

Linux

Linux
OS X
Solaris
Windows

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL-like DML and DDL statements (CQL); Spark SQL

Via inetgration in SQL Server

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

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

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

.NET Client API

Supported programming languages

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

C#
Java

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

Sharding

no "single point of failure"

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware, advanced replication for edge computing

selectable replication factor

Multi-source replication

Multi-source replication
Source-replica replication

none

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

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

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

Access rights for users can be defined per object

Can implement custom security layer via applications

rights management via user accounts

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

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more

Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
» more

Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
» more

Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more

Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more

Licensing and pricing models

Annual subscription
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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