DBMS > ArcadeDB vs. Databend vs. H2GIS vs. RocksDB vs. Transwarp ArgoDB

System Properties Comparison ArcadeDB vs. Databend vs. H2GIS vs. RocksDB vs. Transwarp ArgoDB

Editorial information provided by DB-Engines

Name

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Spatial extension of H2

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Secondary database models

Relational DBMS

Search engine

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

Score	0.10
Rank	#358	Overall
	#48	Document stores
	#38	Graph DBMS
	#52	Key-value stores
	#35	Time Series DBMS

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.12
Rank	#348	Overall
	#151	Relational DBMS

Website

arcadedb.com

github.com/datafuselabs/databend
www.databend.com

www.h2gis.org

rocksdb.org

www.transwarp.cn/en/product/argodb

Technical documentation

docs.arcadedb.com

docs.databend.com

www.h2gis.org/docs/home

github.com/facebook/rocksdb/wiki

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

Arcade Data

Databend Labs

CNRS

Facebook, Inc.

Transwarp

Initial release

2021

2013

Current release

September 2021

1.0.59, April 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

LGPL 3.0

Open Source

BSD

commercial

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

Java

C++

Server operating systems

All OS with a Java VM

hosted
Linux
macOS

Linux

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

SQL

Support of SQL

SQL-like query language, no joins

yes

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

CLI Client
JDBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

Java

Go
Java
JavaScript (Node.js)
Python
Rust

Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

based on H2

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

ACID

yes

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

Users with fine-grained authorization concept, user roles

yes

based on H2

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