DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Brytlyt vs. GridDB vs. PouchDB vs. RocksDB

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Brytlyt vs. GridDB vs. PouchDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

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

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

JavaScript DBMS with an API inspired by CouchDB

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

Primary database model

Secondary database models

Key-value store
Relational DBMS

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

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

Website

www.alibabacloud.com/product/hybriddb-postgresql

Technical documentation

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

docs.brytlyt.io

docs.griddb.net

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Brytlyt

Toshiba Corporation

Apache Software Foundation

Facebook, Inc.

Initial release

2016

2013

2012

2013

Current release

5.0, August 2023

5.1, August 2022

7.1.1, June 2019

9.2.1, May 2024

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

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++ and CUDA

C++

JavaScript

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux

server-less, requires a JavaScript environment (browser, Node.js)

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

via views

SQL

Support of SQL

yes

SQL92, SQL-like TQL (Toshiba Query Language)

APIs and other access methods

JDBC
ODBC

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

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java API

Supported programming languages

C
Java
Perl
Python
R

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

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

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

in PL/pgSQL

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

ACID at container level

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

Access rights for users can be defined per database

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.