DBMS > Atos Standard Common Repository vs. GreptimeDB vs. LevelDB vs. RavenDB vs. RDF4J

System Properties Comparison Atos Standard Common Repository vs. GreptimeDB vs. LevelDB vs. RavenDB vs. RDF4J

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Primary database model

Document store
Key-value store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

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

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

greptime.com

github.com/google/leveldb

ravendb.net

rdf4j.org

Technical documentation

docs.greptime.com

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

ravendb.net/docs

rdf4j.org/documentation

Developer

Atos Convergence Creators

Greptime Inc.

Google

Hibernating Rhinos

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

Initial release

2016

2022

2011

2010

2004

Current release

1703

1.23, February 2021

5.4, July 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

AGPL version 3, commercial license available

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

Java

Rust

C++

Java

Server operating systems

Linux

Android
Docker
FreeBSD
Linux
macOS
Windows

Illumos
Linux
OS X
Windows

Linux
macOS
Raspberry Pi
Windows

Linux
OS X
Unix
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free, schema definition possible

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

optional

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

SQL

Support of SQL

yes

SQL-like query language (RQL)

APIs and other access methods

LDAP

gRPC
HTTP API
JDBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

All languages with LDAP bindings

C++
Erlang
Go
Java
JavaScript

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
PHP
Python

Server-side scripts

Stored procedures

Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source 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 or Eventual Consistency depending on configuration

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

ACID, Cluster-wide transaction available

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.

yes

User concepts

Access control

LDAP bind authentication

Simple rights management via user accounts

Authorization levels configured per client per database

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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