DBMS > atoti vs. BoltDB vs. Linter vs. RocksDB

System Properties Comparison atoti vs. BoltDB vs. Linter vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

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

An embedded key-value store for Go.

RDBMS for high security requirements

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

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.59
Rank	#242	Overall
	#10	Object oriented DBMS

Score	0.76
Rank	#224	Overall
	#32	Key-value stores

Score	0.10
Rank	#350	Overall
	#153	Relational DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

atoti.io

github.com/boltdb/bolt

linter.ru

rocksdb.org

Technical documentation

docs.atoti.io

github.com/facebook/rocksdb/wiki

Developer

ActiveViam

relex.ru

Facebook, Inc.

Initial release

2013

1990

2013

Current release

8.11.4, April 2024

License

Commercial or Open Source

commercial

free versions available

Open Source

MIT License

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux

Data scheme

schema-free

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

Multidimensional Expressions (MDX)

yes

APIs and other access methods

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

C++ API
Java API

Supported programming languages

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Python

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

yes

Concurrency

Support for concurrent manipulation of data

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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