DBMS > ArcadeDB vs. BigchainDB vs. OpenMLDB vs. Trafodion

System Properties Comparison ArcadeDB vs. BigchainDB vs. OpenMLDB vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

An open-source machine learning database that provides a feature platform for training and inference

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Document store

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Website

Technical documentation

docs.arcadedb.com

bigchaindb.readthedocs.io/en/latest

openmldb.ai/docs/zh/main

trafodion.apache.org/documentation.html

Developer

Arcade Data

4 Paradigm Inc.

Apache Software Foundation, originally developed by HP

Initial release

2021

2016

2020

2014

Current release

September 2021

2024-2 February 2024

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL v3

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Python

C++, Java, Scala

C++, Java

Server operating systems

All OS with a Java VM

Linux

Data scheme

schema-free

Fixed schema

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
RESTful HTTP API

JDBC
SQLAlchemy

ADO.NET
JDBC
ODBC

Supported programming languages

Java

Go
Haskell
Java
JavaScript
Python
Ruby

C++
Go
Java
Python
Scala

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

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

yes

fine grained access rights according to SQL-standard

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