DBMS > Graph Engine vs. GreptimeDB vs. H2 vs. JanusGraph vs. WakandaDB

System Properties Comparison Graph Engine vs. GreptimeDB vs. H2 vs. JanusGraph vs. WakandaDB

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

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Graph DBMS
Key-value store

Secondary database models

Spatial DBMS

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

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

Technical documentation

www.graphengine.io/docs/manual

docs.greptime.com

www.h2database.com/html/main.html

docs.janusgraph.org

wakanda.github.io/doc

Developer

Microsoft

Greptime Inc.

Thomas Mueller

Linux Foundation; originally developed as Titan by Aurelius

Wakanda SAS

Initial release

2010

2022

2005

2017

2012

Current release

2.2.220, July 2023

0.6.3, February 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache Version 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache 2.0

Open Source

AGPLv3, extended commercial license 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

.NET and C

Rust

Java

C++, JavaScript

Server operating systems

.NET

Android
Docker
FreeBSD
Linux
macOS
Windows

All OS with a Java VM

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free, schema definition possible

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

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

gRPC
HTTP API
JDBC

JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

RESTful HTTP API

Supported programming languages

C#
C++
F#
Visual Basic

C++
Erlang
Go
Java
JavaScript

Java

Clojure
Java
Python

JavaScript

Server-side scripts

Stored procedures

yes

Python

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

Simple rights management via user accounts

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

yes

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

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