DBMS > Amazon Aurora vs. Couchbase vs. Snowflake vs. SpaceTime vs. TimescaleDB

System Properties Comparison Amazon Aurora vs. Couchbase vs. Snowflake vs. SpaceTime vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

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

Cloud-based data warehousing service for structured and semi-structured data

SpaceTime is a spatio-temporal DBMS with a focus on performance.

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

Primary database model

Secondary database models

Document store

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

Relational DBMS

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

aws.amazon.com/rds/aurora

www.couchbase.com

www.snowflake.com

www.mireo.com/spacetime

www.timescale.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

docs.couchbase.com

docs.snowflake.net/manuals/index.html

docs.timescale.com

Developer

Amazon

Couchbase, Inc.

Snowflake Computing Inc.

Mireo

Timescale

Initial release

2015

2011

2014

2020

2017

Current release

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

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open Source

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

commercial

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

C, C++, Go and Erlang

C++

Server operating systems

hosted

Linux
OS X
Windows

hosted

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

SQL

Support of SQL

yes

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

yes

A subset of ANSI SQL is implemented

yes

full PostgreSQL SQL syntax

APIs and other access methods

ADO.NET
JDBC
ODBC

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

CLI Client
JDBC
ODBC

RESTful HTTP API

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

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

C#
C++
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

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

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

via the TAP protocol

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Automatic Sharding

yes

Fixed-grid hypercubes

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

including cross data center replication
Source-replica replication

yes

Real-time block device replication (DRBD)

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Foreign keys

Referential integrity

yes

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

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

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.

Users with fine-grained authorization concept, user roles and pluggable authentication

yes

fine grained access rights according to SQL-standard

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