DBMS > GeoSpock vs. Google BigQuery vs. Memcached vs. OpenQM

System Properties Comparison GeoSpock vs. Google BigQuery vs. Memcached vs. OpenQM

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Spatial and temporal data processing engine for extreme data scale

Large scale data warehouse service with append-only tables

In-memory key-value store, originally intended for caching

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Relational DBMS

Key-value store

Multivalue DBMS

Secondary database models

Time Series DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Website

geospock.com

cloud.google.com/bigquery

www.memcached.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

cloud.google.com/bigquery/docs

github.com/memcached/memcached/wiki

Developer

GeoSpock

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Rocket Software, originally Martin Phillips

Initial release

2010

2003

1993

Current release

2.0, September 2019

1.6.25, March 2024

3.4-12

License

Commercial or Open Source

commercial

Open Source

BSD license

Open Source

GPLv2, extended commercial license available

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, Javascript

Server operating systems

hosted

FreeBSD
Linux
OS X
Unix
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

schema-free

yes

with some exceptions

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

JDBC

RESTful HTTP/JSON API

Proprietary protocol

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Repcached, a Memcached patch, provides this functionallity

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying 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.

User concepts

Access control

Access rights for users can be defined per table

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

Google Cloud Identity & Access Management (IAM)

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights can be defined down to the item level

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