DBMS > Apache Doris vs. Atos Standard Common Repository vs. HEAVY.AI vs. OrientDB vs. SQLite

System Properties Comparison Apache Doris vs. Atos Standard Common Repository vs. HEAVY.AI vs. OrientDB vs. SQLite

Editorial information provided by DB-Engines

Name

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

Description

An MPP-based analytics DBMS embracing the MySQL protocol

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Multi-model DBMS (Document, Graph, Key/Value)

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

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

github.com/heavyai/heavydb
www.heavy.ai

orientdb.org

www.sqlite.org

Technical documentation

github.com/apache/doris/wiki

docs.heavy.ai

www.orientdb.com/docs/last/index.html

www.sqlite.org/docs.html

Developer

Apache Software Foundation, originally contributed from Baidu

Atos Convergence Creators

HEAVY.AI, Inc.

OrientDB LTD; CallidusCloud; SAP

Dwayne Richard Hipp

Initial release

2017

2016

2010

2000

Current release

1.2.2, February 2023

1703

5.10, January 2022

3.2.29, March 2024

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache version 2

Open Source

Public Domain

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++ and CUDA

Java

Server operating systems

Linux

All OS with a Java JDK (>= JDK 6)

server-less

Data scheme

yes

Schema and schema-less with LDAP views

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

dynamic column types

Typing

predefined data types such as float or date

yes

optional

yes

not rigid because of 'dynamic typing' concept.

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, no joins

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
MySQL client

LDAP

JDBC
ODBC
Thrift
Vega

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Java

All languages with LDAP bindings

All languages supporting JDBC/ODBC/Thrift
Python

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

Java, Javascript

Triggers

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

cell division

Sharding

Round robin

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

fine grained access rights according to SQL-standard

LDAP bind authentication

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

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