DBMS > AgensGraph vs. Greenplum vs. GreptimeDB vs. LevelDB vs. RDF4J

System Properties Comparison AgensGraph vs. Greenplum vs. GreptimeDB vs. LevelDB vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

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

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

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Graph DBMS
Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

bitnine.net/agensgraph

greenplum.org

greptime.com

github.com/google/leveldb

rdf4j.org

Technical documentation

bitnine.net/documentation

docs.greenplum.org

docs.greptime.com

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

rdf4j.org/documentation

Developer

Bitnine Global Inc.

Pivotal Software Inc.

Greptime Inc.

Google

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2016

2005

2022

2011

2004

Current release

2.1, December 2018

7.0.0, September 2023

1.23, February 2021

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Rust

C++

Java

Server operating systems

Linux
OS X
Windows

Linux

Android
Docker
FreeBSD
Linux
macOS
Windows

Illumos
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

depending on used data model

yes

schema-free, schema definition possible

schema-free

yes

RDF Schemas

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

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Cypher Query Language
JDBC

JDBC
ODBC

gRPC
HTTP API
JDBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
Java
JavaScript
Python

C
Java
Perl
Python
R

C++
Erlang
Go
Java
JavaScript

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

in-memory storage is supported as well

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

Simple rights management via user accounts

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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