DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Firebase Realtime Database vs. GridDB vs. SQLite vs. VictoriaMetrics

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Firebase Realtime Database vs. GridDB vs. SQLite vs. VictoriaMetrics

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

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

Scalable in-memory time series database optimized for IoT and Big Data

Widely used embeddable, in-process RDBMS

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Secondary database models

Key-value store
Relational DBMS

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

Score	0.79
Rank	#213	Overall
	#101	Relational DBMS

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	1.23
Rank	#165	Overall
	#15	Time Series DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

firebase.google.com/products/realtime-database

griddb.net

www.sqlite.org

victoriametrics.com

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

firebase.google.com/docs/database

docs.griddb.net

www.sqlite.org/docs.html

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Google

acquired by Google 2014

Toshiba Corporation

Dwayne Richard Hipp

VictoriaMetrics

Initial release

2016

2012

2013

2000

2018

Current release

5.1, August 2022

3.46.1 (13 August 2024), August 2024

v1.91, May 2023

License

Commercial or Open Source

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

Public Domain

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++

Server operating systems

hosted

Linux

server-less

FreeBSD
Linux
macOS
OpenBSD

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

not rigid because of 'dynamic typing' concept.

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

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92, SQL-like TQL (Toshiba Query Language)

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

C
Java
Perl
Python
R

Java
JavaScript
Objective-C

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

limited functionality with using 'rules'

Triggers

yes

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

none

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

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

Immediate consistency within container, eventual consistency across containers

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID at container level

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

Access rights for users can be defined per database

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