DBMS > EventStoreDB vs. Firebase Realtime Database vs. StarRocks vs. Trafodion

System Properties Comparison EventStoreDB vs. Firebase Realtime Database vs. StarRocks vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Transactional SQL-on-Hadoop DBMS

Primary database model

Event Store

Document store

Relational DBMS

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

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Website

www.eventstore.com

firebase.google.com/products/realtime-database

www.starrocks.io

trafodion.apache.org

Technical documentation

developers.eventstore.com

firebase.google.com/docs/database

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

trafodion.apache.org/documentation.html

Developer

Event Store Limited

Google

acquired by Google 2014

The Linux Foundation

since Feb 2023

Apache Software Foundation, originally developed by HP

Initial release

2012

2020

2014

Current release

21.2, February 2021

2.5.3, March 2023

2.3.0, February 2019

License

Commercial or Open Source

Open Source

commercial

Open Source

Apache Version 2.0

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

C++, Java

Server operating systems

Linux
Windows

hosted

Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
MySQL protocol

ADO.NET
JDBC
ODBC

Supported programming languages

Java
JavaScript
Objective-C

Java

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions

Java Stored Procedures

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range and hash)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

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

Foreign keys

Referential integrity

yes

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

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard

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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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