DBMS > Google Cloud Spanner vs. Postgres-XL vs. Riak KV vs. searchxml

System Properties Comparison Google Cloud Spanner vs. Postgres-XL vs. Riak KV vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

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

Distributed, fault tolerant key-value store

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

Key-value store

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

Native XML DBMS
Search engine

Secondary database models

Document store
Spatial DBMS

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

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Score	0.00
Rank	#385	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

cloud.google.com/spanner

www.postgres-xl.org

www.searchxml.net/category/products

Technical documentation

cloud.google.com/spanner/docs

www.postgres-xl.org/documentation

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

www.searchxml.net/support/handouts

Developer

Google

OpenSource, formerly Basho Technologies

informationpartners gmbh

Initial release

2017

2014

since 2012, originally named StormDB

2009

2015

Current release

10 R1, October 2018

3.2.0, December 2022

1.0

License

Commercial or Open Source

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

C++

Server operating systems

hosted

Linux
macOS

Linux
OS X

Windows

Data scheme

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

XML type, but no XML query functionality

yes

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

distributed, parallel query execution

APIs and other access methods

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

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

HTTP API
Native Erlang Interface

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

.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++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

user defined functions

Erlang

yes

on the application server

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

selectable replication factor

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

links between data sets can be stored

Transaction concepts

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

ACID

Strict serializable isolation

ACID

MVCC

multiple readers, single writer

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.

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

yes, using Riak Security

Domain, group and role-based access control at the document level and for application services

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More resources

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23 July 2024, InfoWorld

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1 August 2024, InfoQ.com

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1 August 2024, TechTarget

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Basho aims for enterprise operational simplicity with new Data Platform
26 May 2015, diginomica

provided by Google News

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