DBMS > Firebase Realtime Database vs. Graph Engine vs. Microsoft Access vs. SQLite vs. TDengine

System Properties Comparison Firebase Realtime Database vs. Graph Engine vs. Microsoft Access vs. SQLite vs. TDengine

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

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Widely used embeddable, in-process RDBMS

Time Series DBMS and big data platform

Primary database model

Document store

Graph DBMS
Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Relational 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	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

firebase.google.com/products/realtime-database

www.graphengine.io

www.microsoft.com/en-us/microsoft-365/access

www.sqlite.org

github.com/taosdata/TDengine
tdengine.com

Technical documentation

firebase.google.com/docs/database

www.graphengine.io/docs/manual

developer.microsoft.com/en-us/access

www.sqlite.org/docs.html

docs.tdengine.com

Developer

Google

acquired by Google 2014

Microsoft

Dwayne Richard Hipp

TDEngine, previously Taos Data

Initial release

2012

2010

1992

2000

2019

Current release

1902 (16.0.11328.20222), March 2019

3.45.3 (15 April 2024), April 2024

3.0, August 2022

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

Bundled with Microsoft Office

Open Source

Public Domain

Open Source

AGPL V3, also commercial editions 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

C++

Server operating systems

hosted

.NET

Windows

Not a real database server, but making use of DLLs

server-less

Linux
Windows

Data scheme

schema-free

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

yes

but not compliant to any SQL standard

yes

SQL-92 is not fully supported

Standard SQL with extensions for time-series applications

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

JDBC
RESTful HTTP API

Supported programming languages

Java
JavaScript
Objective-C

C#
C++
F#
Visual Basic

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

since Access 2010 using the ACE-engine

Triggers

Callbacks are triggered when data changes

yes

since Access 2010 using the ACE-engine

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

but no files for transaction logging

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

but no files for transaction logging

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

a simple user-level security was built in till version Access 2003

yes

More information provided by the system vendor

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Market metrics

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Licensing and pricing models

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