DBMS > NSDb vs. openGauss vs. Splice Machine vs. SwayDB vs. Transbase

System Properties Comparison NSDb vs. openGauss vs. Splice Machine vs. SwayDB vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

nsdb.io

gitee.com/opengauss
opengauss.org

splicemachine.com

swaydb.simer.au

www.transaction.de/en/products/transbase.html

Technical documentation

nsdb.io/Architecture

docs.opengauss.org/en
gitee.com/opengauss/docs

splicemachine.com/how-it-works

www.transaction.de/en/products/transbase/features.html

Developer

Huawei and openGauss community

Splice Machine

Simer Plaha

Transaction Software GmbH

Initial release

2017

2019

2014

2018

1987

Current release

3.0, March 2022

3.1, March 2021

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL 3.0, commercial license available

Open Source

GNU Affero GPL V3.0

commercial

free development license

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, Scala

C, C++, Java

Java

Scala

C and C++

Server operating systems

Linux
macOS

Linux

Linux
OS X
Solaris
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

ANSI SQL 2011

yes

APIs and other access methods

gRPC
HTTP REST
WebSocket

JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java
Scala

C
C++
Java

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

Java
Kotlin
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash)

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

none

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of operations

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

Using Apache Lucene

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, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

openGauss Open Source Community Officially Launch
1 July 2020, Huawei

The openGauss powers database industry forward through innovation
6 January 2022, Global Times

Engineering Students from Thammasat Win 2 'Huawei ICT' Awards to Represent Thailand in Asia-Pacific Competition.
12 January 2024, tu.ac.th

Diversified Computing: Open Innovation for Shared Success
30 September 2020, Huawei

Ethiopian Students Finish third in Global ICT Competition – Ethiopian Monitor
29 May 2023, Ethiopian Monitor

provided by Google News

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine ...
19 January 2021, PR Newswire

Splice Machine Launches Feature Store to Simplify Feature Engineering
19 January 2021, Datanami

Real-time machine learning with Splice Machine's ML Manager
17 April 2019, TechTarget

How To Axe Db2 But Keep Your Code
10 March 2020, Towards Data Science

provided by Google News

Share this page