DBMS > Citus vs. Google Cloud Firestore vs. Hazelcast vs. MySQL vs. TerminusDB

System Properties Comparison Citus vs. Google Cloud Firestore vs. Hazelcast vs. MySQL vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

A widely adopted in-memory data grid

Widely used open source RDBMS

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Key/Value like access via memcached API

Graph DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

Document store
RDF store

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

www.citusdata.com

firebase.google.com/products/firestore

hazelcast.com

www.mysql.com

terminusdb.com

Technical documentation

docs.citusdata.com

firebase.google.com/docs/firestore

hazelcast.org/imdg/docs

dev.mysql.com/doc

terminusdb.github.io/terminusdb/#

Developer

Google

Hazelcast

Oracle

since 2010, originally MySQL AB, then Sun

DataChemist Ltd.

Initial release

2010

2017

2008

1995

2018

Current release

8.1, December 2018

5.3.6, November 2023

8.4.0, April 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

Prolog, Rust

Server operating systems

Linux

hosted

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

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

specific XML type available, but no XML query functionality

yes

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

SQL-like query language

yes

with proprietary extensions

SQL-like query language (WOQL)

APIs and other access methods

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

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes, Firebase Rules & Cloud Functions

yes

Event Listeners, Executor Services

yes

proprietary syntax

yes

Triggers

yes

yes, with Cloud Functions

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication

yes

Replicated Map

Multi-source replication
Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

yes

one or two-phase-commit; repeatable reads; read commited

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

in-memory journaling

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

Role-based access control

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