DBMS > Splice Machine vs. Tibero vs. Transwarp StellarDB vs. YTsaurus

System Properties Comparison Splice Machine vs. Tibero vs. Transwarp StellarDB vs. YTsaurus

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Editorial information provided by DB-Engines

Name

Description

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

A secure RDBMS, designed for easy portability from Oracle

A distributed graph DBMS built for enterprise-level graph applications

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Relational DBMS

Graph DBMS

Document store
Key-value store

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

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Score	0.07
Rank	#371	Overall
	#39	Graph DBMS

Score	0.21
Rank	#324	Overall
	#45	Document stores
	#48	Key-value stores

Website

splicemachine.com

us.tmaxsoft.com/products/tibero

www.transwarp.cn/en/product/stellardb

ytsaurus.tech

Technical documentation

splicemachine.com/how-it-works

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

ytsaurus.tech/docs/en

Developer

Splice Machine

TmaxSoft

Transwarp

Yandex

Initial release

2014

2003

2023

Current release

3.1, March 2021

6, April 2015

License

Commercial or Open Source

Open Source

AGPL 3.0, commercial license available

commercial

Open Source

Apache License, Version 2.0

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 and Assembler

C++

Server operating systems

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

Ubuntu

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

YQL, an SQL-based language, is supported

APIs and other access methods

JDBC
Native Spark Datasource
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

OpenCypher

Supported programming languages

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

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

yes

Java

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Shared Nothhing Auto-Sharding, Columnar Partitioning

horizontal partitioning

by range, hash, list or composite

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

yes

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

Concurrency

Support for concurrent manipulation of data

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

planned for next version

User concepts

Access control

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

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

yes

Access Control Lists

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More resources

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