DBMS > NuoDB vs. RocksDB vs. Sadas Engine vs. Splice Machine

System Properties Comparison NuoDB vs. RocksDB vs. Sadas Engine vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Primary database model

Relational DBMS

Key-value store

Relational DBMS

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

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

www.3ds.com/nuodb-distributed-sql-database

rocksdb.org

www.sadasengine.com

splicemachine.com

Technical documentation

doc.nuodb.com

github.com/facebook/rocksdb/wiki

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

splicemachine.com/how-it-works

Developer

Dassault Systèmes

originally NuoDB, Inc.

Facebook, Inc.

SADAS s.r.l.

Splice Machine

Initial release

2013

2006

2014

Current release

9.2.1, May 2024

8.0

3.1, March 2021

License

Commercial or Open Source

commercial

limited edition free

Open Source

BSD

commercial

free trial version available

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

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Implementation language

C++

Java

Server operating systems

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux

AIX
Linux
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

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

APIs and other access methods

ADO.NET
JDBC
ODBC

C++ API
Java API

JDBC
ODBC
Proprietary protocol

JDBC
Native Spark Datasource
ODBC

Supported programming languages

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

C
C++
Go
Java
Perl
Python
Ruby

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

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

Server-side scripts

Stored procedures

Java, SQL

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

data is dynamically stored/cached on the nodes where it is read/written

horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Managed transparently by NuoDB

yes

none

Multi-source replication
Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

tunable commit protocol

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

yes, multi-version concurrency control (MVCC)

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

Temporary table

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

Standard SQL roles/ privileges, Administrative Users

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

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