DBMS > BigObject vs. OpenMLDB vs. Sadas Engine vs. ToroDB

System Properties Comparison BigObject vs. OpenMLDB vs. Sadas Engine vs. ToroDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for real-time computations and queries

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Relational DBMS

Document store

Secondary database models

Relational DBMS

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

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	0.11
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

bigobject.io

openmldb.ai

www.sadasengine.com

github.com/torodb/server

Technical documentation

docs.bigobject.io

openmldb.ai/docs/zh/main

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

BigObject, Inc.

4 Paradigm Inc.

SADAS s.r.l.

8Kdata

Initial release

2015

2020

2006

2016

Current release

2024-2 February 2024

8.0

License

Commercial or Open Source

commercial

free community edition available

Open Source

commercial

free trial version available

Open Source

AGPL-V3

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

C++, Java, Scala

C++

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

AIX
Linux
Windows

All OS with a Java 7 VM

Data scheme

yes

Fixed schema

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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 DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
SQLAlchemy

JDBC
ODBC
Proprietary protocol

Supported programming languages

C++
Go
Java
Python
Scala

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

Lua

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

Access rights for users and roles

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