DBMS > Apache Doris vs. Atos Standard Common Repository vs. BigObject vs. GreptimeDB

System Properties Comparison Apache Doris vs. Atos Standard Common Repository vs. BigObject vs. GreptimeDB

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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

Analytic DBMS for real-time computations and queries

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

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

Score	0.61
Rank	#235	Overall
	#110	Relational DBMS

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	0.09
Rank	#343	Overall
	#31	Time Series DBMS

Website

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

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

bigobject.io

greptime.com

Technical documentation

github.com/apache/doris/wiki

docs.bigobject.io

docs.greptime.com

Developer

Apache Software Foundation, originally contributed from Baidu

Atos Convergence Creators

BigObject, Inc.

Greptime Inc.

Initial release

2017

2016

2015

2022

Current release

1.2.2, February 2023

1703

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community edition available

Open Source

Apache Version 2.0

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

Rust

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Android
Docker
FreeBSD
Linux
macOS
Windows

Data scheme

yes

Schema and schema-less with LDAP views

yes

schema-free, schema definition possible

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

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
MySQL client

LDAP

fluentd
ODBC
RESTful HTTP API

gRPC
HTTP API
JDBC

Supported programming languages

Java

All languages with LDAP bindings

C++
Erlang
Go
Java
JavaScript

Server-side scripts

Stored procedures

user defined functions

Lua

Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

cell division

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

Atomic execution of specific operations

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

User concepts

Access control

fine grained access rights according to SQL-standard

LDAP bind authentication

Simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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More resources

Recent citations in the news

Migrating from ClickHouse to Apache Doris: Boosting OLAP Performance
9 October 2023, hackernoon.com

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

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

Apache Doris Analytical Database Graduates from Apache Incubator
20 June 2022, Datanami

StarRocks’ real-time analytics engine moves to the cloud
14 July 2022, SiliconANGLE News

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