DBMS > Amazon Redshift vs. Couchbase vs. GridGain vs. PouchDB vs. Warp 10

System Properties Comparison Amazon Redshift vs. Couchbase vs. GridGain vs. PouchDB vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

GridGain is an in-memory computing platform, built on Apache Ignite

JavaScript DBMS with an API inspired by CouchDB

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Document store

Key-value store
Relational DBMS

Document store

Time Series DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

docs.couchbase.com

www.gridgain.com/docs/index.html

pouchdb.com/guides

www.warp10.io/content/02_Getting_started

Developer

Amazon (based on PostgreSQL)

Couchbase, Inc.

GridGain Systems, Inc.

Apache Software Foundation

SenX

Initial release

2012

2011

2007

2012

2015

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

GridGain 8.5.1

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Open Source

Apache License 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, C++, Go and Erlang

Java, C++, .Net

JavaScript

Java

Server operating systems

hosted

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

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

Linux
OS X
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

Secondary indexes

restricted

yes

via views

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

JDBC
ODBC

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP REST

only for PouchDB Server
JavaScript API

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript

Server-side scripts

Stored procedures

user defined functions

in Python

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes (compute grid and cache interceptors can be used instead)

View functions in JavaScript

yes

WarpScript

Triggers

yes

via the TAP protocol

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

yes (replicated cache)

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Eventual Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

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

Ephemeral buckets

yes

User concepts

Access control

fine grained access rights according to SQL-standard

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Security Hooks for custom implementations

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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