DBMS > Graph Engine vs. Sadas Engine vs. TerarkDB vs. Transwarp Hippo

System Properties Comparison Graph Engine vs. Sadas Engine vs. TerarkDB vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Graph DBMS
Key-value store

Relational DBMS

Key-value store

Vector DBMS

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

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Score	0.05
Rank	#386	Overall
	#16	Vector DBMS

Website

www.graphengine.io

www.sadasengine.com

github.com/bytedance/terarkdb

www.transwarp.cn/en/subproduct/hippo

Technical documentation

www.graphengine.io/docs/manual

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

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Microsoft

SADAS s.r.l.

ByteDance, originally Terark

Initial release

2010

2006

2016

2023

Current release

8.0

1.0, May 2023

License

Commercial or Open Source

Open Source

MIT License

commercial

free trial version available

commercial

restricted open source version available

commercial

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

.NET and C

C++

Server operating systems

.NET

AIX
Linux
Windows

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

RESTful HTTP API

JDBC
ODBC
Proprietary protocol

C++ API
Java API

RESTful HTTP API

Supported programming languages

C#
C++
F#
Visual Basic

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

C++
Java

C++
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

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

Role based access control and fine grained access rights

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More resources

Recent citations in the news

Trinity
30 October 2010, Microsoft

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13 February 2017, InfoWorld

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