DBMS > Apache Doris vs. Atos Standard Common Repository vs. SpaceTime vs. SQL.JS

System Properties Comparison Apache Doris vs. Atos Standard Common Repository vs. SpaceTime vs. SQL.JS

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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

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Port of SQLite to JavaScript

Primary database model

Relational DBMS

Document store
Key-value store

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Website

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

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

www.mireo.com/spacetime

sql.js.org

Technical documentation

github.com/apache/doris/wiki

sql.js.org/documentation/index.html

Developer

Apache Software Foundation, originally contributed from Baidu

Atos Convergence Creators

Mireo

Alon Zakai

enhancements implemented by others

Initial release

2017

2016

2020

2012

Current release

1.2.2, February 2023

1703

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

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++

JavaScript

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

yes

optional

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
MySQL client

LDAP

RESTful HTTP API

JavaScript API

Supported programming languages

Java

All languages with LDAP bindings

C#
C++
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

cell division

Fixed-grid hypercubes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Real-time block device replication (DRBD)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

none

Foreign keys

Referential integrity

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

Durability

Support for making data persistent

yes

except by serializing a db to a file

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

yes

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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Recent citations in the news

Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB?
5 June 2024, hackernoon.com

Workload Isolation in Apache Doris: Optimizing Resource Management and Performance
25 May 2024, hackernoon.com

How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second
1 September 2023, KDnuggets

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24 June 2022, InfoWorld

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8 May 2024, hackernoon.com

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