DBMS > Amazon DocumentDB vs. Amazon Redshift vs. Geode vs. TimescaleDB

System Properties Comparison Amazon DocumentDB vs. Amazon Redshift vs. Geode vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Large scale data warehouse service for use with business intelligence tools

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Secondary database models

Relational DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

aws.amazon.com/documentdb

aws.amazon.com/redshift

geode.apache.org

www.timescale.com

Technical documentation

aws.amazon.com/documentdb/resources

docs.aws.amazon.com/redshift

geode.apache.org/docs

docs.timescale.com

Developer

Amazon (based on PostgreSQL)

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Timescale

Initial release

2019

2012

2002

2017

Current release

1.1, February 2017

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache 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

Java

Server operating systems

hosted

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language (OQL)

yes

full PostgreSQL SQL syntax

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC

Java Client API
Memcached protocol
RESTful HTTP API

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

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

All languages supporting JDBC/ODBC

.Net
All JVM based languages
C++
Groovy
Java
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes

Multi-source replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

informational only, not enforced by the system

yes

Transaction concepts

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

Atomic single-document operations

ACID

yes, on a single node

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.

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Access rights per client and object definable

fine grained access rights according to SQL-standard

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