DBMS > Firebase Realtime Database vs. Graph Engine vs. JanusGraph vs. LevelDB vs. Microsoft SQL Server

System Properties Comparison Firebase Realtime Database vs. Graph Engine vs. JanusGraph vs. LevelDB vs. Microsoft SQL Server

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Microsofts flagship relational DBMS

Primary database model

Document store

Graph DBMS
Key-value store

Graph DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Graph DBMS
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	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

firebase.google.com/products/realtime-database

www.graphengine.io

janusgraph.org

github.com/google/leveldb

www.microsoft.com/en-us/sql-server

Technical documentation

firebase.google.com/docs/database

www.graphengine.io/docs/manual

docs.janusgraph.org

github.com/google/leveldb/blob/main/doc/index.md

learn.microsoft.com/en-US/sql/sql-server

Developer

Google

acquired by Google 2014

Microsoft

Linux Foundation; originally developed as Titan by Aurelius

Google

Microsoft

Initial release

2012

2010

2017

2011

1989

Current release

0.6.3, February 2023

1.23, February 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache 2.0

Open Source

BSD

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

.NET and C

Java

C++

Server operating systems

hosted

.NET

Linux
OS X
Unix
Windows

Illumos
Linux
OS X
Windows

Linux
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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Java
JavaScript
Objective-C

C#
C++
F#
Visual Basic

Clojure
Java
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

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

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

with automatic compression on writes

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

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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