DBMS > EDB Postgres vs. Google Cloud Firestore vs. RocksDB vs. Sphinx

System Properties Comparison EDB Postgres vs. Google Cloud Firestore vs. RocksDB vs. Sphinx

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

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.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.91
Rank	#130	Overall
	#60	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

www.enterprisedb.com

firebase.google.com/products/firestore

rocksdb.org

sphinxsearch.com

Technical documentation

www.enterprisedb.com/docs

firebase.google.com/docs/firestore

github.com/facebook/rocksdb/wiki

sphinxsearch.com/docs

Developer

EnterpriseDB

Google

Facebook, Inc.

Sphinx Technologies Inc.

Initial release

2005

2017

2013

2001

Current release

14, December 2021

9.2.1, May 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

commercial

Open Source

BSD

Open Source

GPL version 2, commercial licence available

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++

Server operating systems

Linux
Windows

hosted

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

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.

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

standard with numerous extensions

SQL-like query language (SphinxQL)

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

C++ API
Java API

Proprietary protocol

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

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

C
C++
Go
Java
Perl
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

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

Triggers

yes

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

by hash, list or range

Sharding

horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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.

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.