DBMS > BoltDB vs. FatDB vs. Percona Server for MongoDB vs. Qdrant vs. RocksDB

System Properties Comparison BoltDB vs. FatDB vs. Percona Server for MongoDB vs. Qdrant vs. RocksDB

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

An embedded key-value store for Go.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

A high-performance vector database with neural network or semantic-based matching

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

Primary database model

Key-value store

Document store
Key-value store

Document store

Vector DBMS

Key-value store

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

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

Score	0.60
Rank	#246	Overall
	#39	Document stores

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

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

Website

github.com/boltdb/bolt

www.percona.com/mongodb/software/percona-server-for-mongodb

github.com/qdrant/qdrant
qdrant.tech

rocksdb.org

Technical documentation

docs.percona.com/percona-distribution-for-mongodb

qdrant.tech/documentation

github.com/facebook/rocksdb/wiki

Developer

FatCloud

Percona

Qdrant

Facebook, Inc.

Initial release

2013

2012

2015

2021

2013

Current release

3.4.10-2.10, November 2017

9.2.1, May 2024

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

GPL Version 2

Open Source

Apache Version 2.0

Open Source

BSD

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

C++

Rust

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Windows

Linux

Docker
Linux
macOS
Windows

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

Via inetgration in SQL Server

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

proprietary protocol using JSON

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

C++ API
Java API

Supported programming languages

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

via applications

JavaScript

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Source-replica replication

Collection-level replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Eventual Consistency, tunable consistency

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

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

via In-Memory Engine

yes

User concepts

Access control

Can implement custom security layer via applications

Access rights for users and roles

Key-based authentication

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