DBMS > AgensGraph vs. Brytlyt vs. Firebase Realtime Database vs. InfluxDB vs. Microsoft Azure Cosmos DB

System Properties Comparison AgensGraph vs. Brytlyt vs. Firebase Realtime Database vs. InfluxDB vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

DBMS for storing time series, events and metrics

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Document store

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

with GEO package

Spatial DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

bitnine.net/agensgraph

brytlyt.io

firebase.google.com/products/realtime-database

www.influxdata.com/products/influxdb-overview

azure.microsoft.com/services/cosmos-db

Technical documentation

bitnine.net/documentation

docs.brytlyt.io

firebase.google.com/docs/database

docs.influxdata.com/influxdb

learn.microsoft.com/azure/cosmos-db

Developer

Bitnine Global Inc.

Brytlyt

Google

acquired by Google 2014

Microsoft

Initial release

2016

2012

2013

2014

Current release

2.1, December 2018

5.0, August 2023

2.7.6, April 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

MIT-License; commercial enterprise version available

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 CUDA

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X

through Homebrew

hosted

Data scheme

depending on used data model

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

JSON types

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

Cypher Query Language
JDBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Android
iOS
JavaScript API
RESTful HTTP API

HTTP API
JSON over UDP

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

C
Java
JavaScript
Python

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Java
JavaScript
Objective-C

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes

user defined functions

in PL/pgSQL

limited functionality with using 'rules'

JavaScript

Triggers

yes

Callbacks are triggered when data changes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

in enterprise version only

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

in enterprise version only

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Multi-item ACID transactions with snapshot isolation within a partition

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.

yes

Depending on used storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

simple rights management via user accounts

Access rights can be defined down to the item level

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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