DBMS > HugeGraph vs. OpenQM vs. Sadas Engine vs. YugabyteDB

System Properties Comparison HugeGraph vs. OpenQM vs. Sadas Engine vs. YugabyteDB

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Editorial information provided by DB-Engines

Name

Description

A fast-speed and highly-scalable Graph DBMS

QpenQM is a high-performance, self-tuning, multi-value DBMS

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

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Graph DBMS

Multivalue DBMS

Relational DBMS

Secondary database models

Document store
Wide column store

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

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	2.91
Rank	#102	Overall
	#51	Relational DBMS

Website

github.com/hugegraph
hugegraph.apache.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.sadasengine.com

www.yugabyte.com

Technical documentation

hugegraph.apache.org/docs

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

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

Baidu

Rocket Software, originally Martin Phillips

SADAS s.r.l.

Yugabyte Inc.

Initial release

2018

1993

2006

2017

Current release

0.9

3.4-12

8.0

2.19, September 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPLv2, extended commercial license available

commercial

free trial version available

Open Source

Apache 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.

YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.

Implementation language

Java

C++

C and C++

Server operating systems

Linux
macOS
Unix

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

AIX
Linux
Windows

Linux
OS X

Data scheme

yes

with some exceptions

yes

depending on used data model

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

yes, PostgreSQL compatible

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

JDBC
ODBC
Proprietary protocol

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

Supported programming languages

Groovy
Java
Python

.Net
Basic
C
Java
Objective C
PHP
Python

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

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

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

sql, plpgsql, C

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

horizontal partitioning

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

yes

none

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

based on RocksDB

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'

User concepts

Access control

Users, roles and permissions

Access rights can be defined down to the item level

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

yes

More information provided by the system vendor

Specific characteristics

YugabyteDB is an open source distributed SQL database for cloud native transactional...
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Competitive advantages

PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
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Typical application scenarios

Systems of record and engagement for cloud native applications that require resilience,...
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Market metrics

2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
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Licensing and pricing models

Apache 2.0 license for the database
» more

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