DBMS > Badger vs. Firebase Realtime Database vs. Heroic vs. Microsoft Azure Synapse Analytics vs. Newts

System Properties Comparison Badger vs. Firebase Realtime Database vs. Heroic vs. Microsoft Azure Synapse Analytics vs. Newts

Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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

Time Series DBMS based on Cassandra

Primary database model

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

github.com/dgraph-io/badger

firebase.google.com/products/realtime-database

github.com/spotify/heroic

azure.microsoft.com/services/synapse-analytics

opennms.github.io/newts

Technical documentation

godoc.org/github.com/dgraph-io/badger

firebase.google.com/docs/database

spotify.github.io/heroic

docs.microsoft.com/azure/synapse-analytics

github.com/OpenNMS/newts/wiki

Developer

DGraph Labs

Google

acquired by Google 2014

Spotify

Microsoft

OpenNMS Group

Initial release

2017

2012

2014

2016

2014

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

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

Java

C++

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
ODBC

HTTP REST
Java API

Supported programming languages

Java
JavaScript
Objective-C

C#
Java
PHP

Java

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Transact SQL

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Sharding, horizontal partitioning

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

selectable replication factor

based on Cassandra

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

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

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.

User concepts

Access control

yes, based on authentication and database rules

yes

More information provided by the system vendor

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Related products and services

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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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