DBMS > Google BigQuery vs. Memcached vs. OpenQM vs. OrigoDB vs. TerminusDB

System Properties Comparison Google BigQuery vs. Memcached vs. OpenQM vs. OrigoDB vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

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

A fully ACID in-memory object graph database

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Key-value store

Multivalue DBMS

Document store
Object oriented DBMS

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

cloud.google.com/bigquery

www.memcached.org

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

origodb.com

terminusdb.com

Technical documentation

cloud.google.com/bigquery/docs

github.com/memcached/memcached/wiki

origodb.com/docs

terminusdb.github.io/terminusdb/#

Developer

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Rocket Software, originally Martin Phillips

Robert Friberg et al

DataChemist Ltd.

Initial release

2010

2003

1993

2009

under the name LiveDB

2018

Current release

1.6.25, March 2024

3.4-12

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

BSD license

Open Source

GPLv2, extended commercial license available

Open Source

GPL V3

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

Prolog, Rust

Server operating systems

hosted

FreeBSD
Linux
OS X
Unix
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
Windows

Linux

Data scheme

yes

schema-free

yes

with some exceptions

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language (WOQL)

APIs and other access methods

RESTful HTTP/JSON API

Proprietary protocol

.NET Client API
HTTP API
LINQ

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

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

.Net

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

horizontal partitioning

client side managed; servers are not synchronized

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Repcached, a Memcached patch, provides this functionallity

yes

Source-replica replication

Journaling Streams

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

depending on model

yes

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

Write ahead log

yes

in-memory journaling

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 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

Role based authorization

Role-based access control

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