DBMS > Amazon DynamoDB vs. Google BigQuery vs. Postgres-XL vs. Riak KV vs. TimesTen

System Properties Comparison Amazon DynamoDB vs. Google BigQuery vs. Postgres-XL vs. Riak KV vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Large scale data warehouse service with append-only tables

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Distributed, fault tolerant key-value store

In-Memory RDBMS compatible to Oracle

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

aws.amazon.com/dynamodb

cloud.google.com/bigquery

www.postgres-xl.org

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.aws.amazon.com/dynamodb

cloud.google.com/bigquery/docs

www.postgres-xl.org/documentation

www.tiot.jp/riak-docs/riak/kv/latest

docs.oracle.com/database/timesten-18.1

Developer

Amazon

Google

OpenSource, formerly Basho Technologies

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2012

2010

2014

since 2012, originally named StormDB

2009

1998

Current release

10 R1, October 2018

3.2.0, December 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Mozilla public license

Open Source

Apache version 2, commercial enterprise edition

commercial

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

Erlang

Server operating systems

hosted

Linux
macOS

Linux
OS X

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

schema-free

yes

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

XML type, but no XML query functionality

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

RESTful HTTP API

RESTful HTTP/JSON API

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

HTTP API
Native Erlang Interface

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions

Erlang

PL/SQL

Triggers

yes

by integration with AWS Lambda

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

Since BigQuery is designed for querying data

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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 can be defined via the AWS Identity and Access Management (IAM)

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

yes, using Riak Security

fine grained access rights according to SQL-standard

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