DBMS > Geode vs. HugeGraph vs. LevelDB vs. Newts vs. Sadas Engine

System Properties Comparison Geode vs. HugeGraph vs. LevelDB vs. Newts vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

A fast-speed and highly-scalable Graph DBMS

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Time Series DBMS based on Cassandra

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

Primary database model

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

geode.apache.org

github.com/hugegraph
hugegraph.apache.org

github.com/google/leveldb

opennms.github.io/newts

www.sadasengine.com

Technical documentation

geode.apache.org/docs

hugegraph.apache.org/docs

github.com/google/leveldb/blob/main/doc/index.md

github.com/OpenNMS/newts/wiki

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

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Baidu

Google

OpenNMS Group

SADAS s.r.l.

Initial release

2002

2018

2011

2014

2006

Current release

1.1, February 2017

0.9

1.23, February 2021

8.0

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

Apache 2.0

commercial

free trial version available

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++

Java

C++

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

Linux
macOS
Unix

Illumos
Linux
OS X
Windows

Linux
OS X
Windows

AIX
Linux
Windows

Data scheme

schema-free

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

also supports composite index and range index

yes

SQL

Support of SQL

SQL-like query language (OQL)

yes

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP REST
Java API

JDBC
ODBC
Proprietary protocol

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

Groovy
Java
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Java

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

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

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

none

Sharding

based on Cassandra

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

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

none

selectable replication factor

based on Cassandra

none

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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'

User concepts

Access control

Access rights per client and object definable

Users, roles and permissions

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

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