DBMS > BoltDB vs. Drizzle vs. Firebase Realtime Database vs. Kinetica vs. PostgreSQL

System Properties Comparison BoltDB vs. Drizzle vs. Firebase Realtime Database vs. Kinetica vs. PostgreSQL

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

An embedded key-value store for Go.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Fully vectorized database across both GPUs and CPUs

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Website

github.com/boltdb/bolt

firebase.google.com/products/realtime-database

www.kinetica.com

www.postgresql.org

Technical documentation

firebase.google.com/docs/database

docs.kinetica.com

www.postgresql.org/docs

Developer

Drizzle project, originally started by Brian Aker

Google

acquired by Google 2014

Kinetica

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2013

2008

2012

1989

1989: Postgres, 1996: PostgreSQL

Current release

7.2.4, September 2012

7.1, August 2021

16.3, May 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

GNU GPL

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

C, C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X

hosted

Linux

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Data scheme

schema-free

yes

schema-free

yes

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements

yes

standard with numerous extensions

APIs and other access methods

JDBC

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C
C++
Java
PHP

Java
JavaScript
Objective-C

C++
Java
JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

hooks for callbacks inside the server can be used.

Callbacks are triggered when data changes

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

yes

ACID

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

GPU vRAM or System RAM

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes, based on authentication and database rules

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

More information provided by the system vendor

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Related products and services

3rd parties

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