DBMS > Brytlyt vs. Firebase Realtime Database vs. GeoMesa vs. PostgreSQL vs. TerarkDB

System Properties Comparison Brytlyt vs. Firebase Realtime Database vs. GeoMesa vs. PostgreSQL vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

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.

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Key-value store

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

brytlyt.io

firebase.google.com/products/realtime-database

www.geomesa.org

www.postgresql.org

github.com/bytedance/terarkdb

Technical documentation

docs.brytlyt.io

firebase.google.com/docs/database

www.geomesa.org/documentation/stable/user/index.html

www.postgresql.org/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Brytlyt

Google

acquired by Google 2014

CCRi and others

PostgreSQL Global Development Group

www.postgresql.org/developer

ByteDance, originally Terark

Initial release

2016

2012

2014

1989

1989: Postgres, 1996: PostgreSQL

2016

Current release

5.0, August 2023

5.0.0, May 2024

16.3, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

BSD

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C, C++ and CUDA

Scala

C++

Server operating systems

Linux
OS X
Windows

hosted

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Data scheme

yes

schema-free

yes

schema-free

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

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

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

APIs and other access methods

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

Android
iOS
JavaScript API
RESTful HTTP API

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

C++ API
Java API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Java
JavaScript
Objective-C

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++
Java

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

limited functionality with using 'rules'

user defined functions

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

Triggers

yes

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

partitioning by range, list and (since PostgreSQL 11) by hash

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

depending on storage layer

Source-replica replication

other methods possible by using 3rd party extensions

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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.

depending on storage layer

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

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