DBMS > Apache Doris vs. atoti vs. BoltDB vs. RocksDB

System Properties Comparison Apache Doris vs. atoti vs. BoltDB vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

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

An embedded key-value store for Go.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Object oriented DBMS

Key-value store

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

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

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

atoti.io

github.com/boltdb/bolt

rocksdb.org

Technical documentation

github.com/apache/doris/wiki

docs.atoti.io

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation, originally contributed from Baidu

ActiveViam

Facebook, Inc.

Initial release

2017

2013

Current release

1.2.2, February 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free versions available

Open Source

MIT License

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

yes

Multidimensional Expressions (MDX)

APIs and other access methods

JDBC
MySQL client

C++ API
Java API

Supported programming languages

Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Python

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding, horizontal partitioning

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

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