DBMS > CockroachDB vs. EsgynDB vs. Firebase Realtime Database vs. Microsoft Azure Cosmos DB vs. Trino

System Properties Comparison CockroachDB vs. EsgynDB vs. Firebase Realtime Database vs. Microsoft Azure Cosmos DB vs. Trino

Editorial information provided by DB-Engines

Name

Description

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Globally distributed, horizontally scalable, multi-model database service

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Relational DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	4.74
Rank	#67	Overall
	#36	Relational DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	24.97
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	5.28
Rank	#61	Overall
	#35	Relational DBMS

Website

www.cockroachlabs.com

www.esgyn.cn

firebase.google.com/products/realtime-database

azure.microsoft.com/services/cosmos-db

trino.io

Technical documentation

www.cockroachlabs.com/docs

firebase.google.com/docs/database

learn.microsoft.com/azure/cosmos-db

trino.io/broadcast
trino.io/docs/current

Developer

Cockroach Labs

Esgyn

Google

acquired by Google 2014

Microsoft

Trino Software Foundation

Initial release

2015

2012

2014

2012

2020 rebranded from PrestoSQL

Current release

24.1.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

Open Source

Apache Version 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

C++, Java

Java

Server operating systems

Linux
macOS
Windows

Linux

hosted

Linux
macOS

for devlopment

Data scheme

dynamic schema

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

depending on connected data-source

SQL

Support of SQL

yes, wire compatible with PostgreSQL

yes

SQL-like query language

yes

APIs and other access methods

JDBC

ADO.NET
JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

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

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript
Objective-C

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

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

limited functionality with using 'rules'

JavaScript

yes, depending on connected data-source

Triggers

Callbacks are triggered when data changes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

Implicit feature of the cloud service

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

Multi-source replication between multi datacenters

yes

Implicit feature of the cloud service

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

depending on connected data-source

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

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

depending on connected data-source

In-memory capabilities

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

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

Access rights can be defined down to the item level

SQL standard access control

More information provided by the system vendor

News

23 is a go, keeping pace with Java
17 September 2024

65: Performance boosts
12 September 2024

64: Control with Open Policy Agent OPA
22 August 2024

63: Querying with JS
1 August 2024

62: A lakehouse that simply works at Prezi
11 July 2024

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