DBMS > Firebase Realtime Database vs. Graph Engine vs. H2 vs. KeyDB vs. WakandaDB

System Properties Comparison Firebase Realtime Database vs. Graph Engine vs. H2 vs. KeyDB vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Document store

Graph DBMS
Key-value store

Relational DBMS

Key-value store

Object oriented DBMS

Secondary database models

Spatial DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

firebase.google.com/products/realtime-database

www.graphengine.io

www.h2database.com

github.com/Snapchat/KeyDB
keydb.dev

wakanda.github.io

Technical documentation

firebase.google.com/docs/database

www.graphengine.io/docs/manual

www.h2database.com/html/main.html

docs.keydb.dev

wakanda.github.io/doc

Developer

Google

acquired by Google 2014

Microsoft

Thomas Mueller

EQ Alpha Technology Ltd.

Wakanda SAS

Initial release

2012

2010

2005

2019

2012

Current release

2.2.220, July 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

BSD-3

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

.NET and C

Java

C++

C++, JavaScript

Server operating systems

hosted

.NET

All OS with a Java VM

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

SQL

Support of SQL

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

RESTful HTTP API

Supported programming languages

Java
JavaScript
Objective-C

C#
C++
F#
Visual Basic

Java

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

JavaScript

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Java Stored Procedures and User-Defined Functions

Lua

yes

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

simple password-based access control and ACL

yes

More information provided by the system vendor

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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