DBMS > atoti vs. OpenMLDB vs. OrigoDB vs. TerarkDB

System Properties Comparison atoti vs. OpenMLDB vs. OrigoDB vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

A fully ACID in-memory object graph database

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Object oriented DBMS

Time Series DBMS

Document store
Object oriented DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

atoti.io

openmldb.ai

origodb.com

github.com/bytedance/terarkdb

Technical documentation

docs.atoti.io

openmldb.ai/docs/zh/main

origodb.com/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

ActiveViam

4 Paradigm Inc.

Robert Friberg et al

ByteDance, originally Terark

Initial release

2020

2009

under the name LiveDB

2016

Current release

2024-2 February 2024

License

Commercial or Open Source

commercial

free versions available

Open Source

commercial

restricted open source version 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

Java

C++, Java, Scala

C++

Server operating systems

Linux

Linux
Windows

Data scheme

Fixed schema

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

APIs and other access methods

JDBC
SQLAlchemy

.NET Client API
HTTP API
LINQ

C++ API
Java API

Supported programming languages

C++
Go
Java
Python
Scala

.Net

C++
Java

Server-side scripts

Stored procedures

Python

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

horizontal partitioning

client side managed; servers are not synchronized

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Write ahead log

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

fine grained access rights according to SQL-standard

Role based authorization

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