DBMS > Firebase Realtime Database vs. Informix vs. KeyDB vs. Microsoft Azure Synapse Analytics

System Properties Comparison Firebase Realtime Database vs. Informix vs. KeyDB vs. Microsoft Azure Synapse Analytics

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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 secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

Document store

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	17.87
Rank	#35	Overall
	#22	Relational DBMS

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

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

firebase.google.com/products/realtime-database

www.ibm.com/products/informix

github.com/Snapchat/KeyDB
keydb.dev

azure.microsoft.com/services/synapse-analytics

Technical documentation

firebase.google.com/docs/database

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

docs.keydb.dev

docs.microsoft.com/azure/synapse-analytics

Developer

Google

acquired by Google 2014

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

EQ Alpha Technology Ltd.

Microsoft

Initial release

2012

1984

2019

2016

Current release

14.10.FC5, November 2020

License

Commercial or Open Source

commercial

free developer edition available

Open Source

BSD-3

commercial

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

C, C++ and Java

C++

Server operating systems

hosted

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux

hosted

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

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

yes

SQL

Support of SQL

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET
JDBC
ODBC

Supported programming languages

Java
JavaScript
Objective-C

.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

C#
Java
PHP

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Lua

Transact SQL

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

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

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

Durability

Support for making data persistent

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

Users with fine-grained authentication, authorization, and auditing controls

simple password-based access control and ACL

yes

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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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