DBMS > Firebase Realtime Database vs. Teradata Aster vs. Transbase vs. YugabyteDB

System Properties Comparison Firebase Realtime Database vs. Teradata Aster vs. Transbase vs. YugabyteDB

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Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

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

Platform for big data analytics on multistructured data sources and types

A resource-optimized, high-performance, universally applicable RDBMS

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Document store

Relational DBMS

Secondary database models

Document store
Wide column store

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

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Score	2.48
Rank	#108	Overall
	#53	Relational DBMS

Website

firebase.google.com/products/realtime-database

www.transaction.de/en/products/transbase.html

www.yugabyte.com

Technical documentation

firebase.google.com/docs/database

www.transaction.de/en/products/transbase/features.html

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

Google

acquired by Google 2014

Teradata

Transaction Software GmbH

Yugabyte Inc.

Initial release

2012

2005

1987

2017

Current release

Transbase 8.3, 2022

2.19, September 2023

License

Commercial or Open Source

commercial

free development license

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.

YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.

Implementation language

C and C++

Server operating systems

hosted

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Linux
OS X

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

yes

depending on used data model

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

yes, PostgreSQL compatible

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

Supported programming languages

Java
JavaScript
Objective-C

C
C#
C++
Java
Python
R

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

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

Server-side scripts

Stored procedures

limited functionality with using 'rules'

R packages

yes

sql, plpgsql, C

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

Source-replica replication

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

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 or Eventual Consistency depending on configuration

Immediate Consistency

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

yes

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

based on RocksDB

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

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

YugabyteDB is an open source distributed SQL database for cloud native transactional...
» more

Competitive advantages

PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
» more

Typical application scenarios

Systems of record and engagement for cloud native applications that require resilience,...
» more

Market metrics

2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
» more

Licensing and pricing models

Apache 2.0 license for the database
» more

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More resources

DB-Engines blog posts

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