DBMS > Google Cloud Bigtable vs. OpenQM vs. OrigoDB vs. VelocityDB vs. Warp 10

System Properties Comparison Google Cloud Bigtable vs. OpenQM vs. OrigoDB vs. VelocityDB vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

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

A fully ACID in-memory object graph database

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Key-value store
Wide column store

Multivalue DBMS

Document store
Object oriented DBMS

Graph DBMS
Object oriented DBMS

Time Series DBMS

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

Score	3.58
Rank	#92	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.33
Rank	#286	Overall
	#10	Multivalue DBMS

Score	0.03
Rank	#378	Overall
	#51	Document stores
	#18	Object oriented DBMS

Score	0.11
Rank	#347	Overall
	#35	Graph DBMS
	#15	Object oriented DBMS

Score	0.08
Rank	#358	Overall
	#35	Time Series DBMS

Website

cloud.google.com/bigtable

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

origodb.com

velocitydb.com

www.warp10.io

Technical documentation

cloud.google.com/bigtable/docs

origodb.com/docs

velocitydb.com/UserGuide

www.warp10.io/content/02_Getting_started

Developer

Google

Rocket Software, originally Martin Phillips

Robert Friberg et al

VelocityDB Inc

SenX

Initial release

2015

1993

2009

under the name LiveDB

2011

2015

Current release

3.4-12

7.x

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

Open Source

commercial

Open Source

Apache License 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

Java

Server operating systems

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
Windows

Any that supports .NET

Linux
OS X
Windows

Data scheme

schema-free

yes

with some exceptions

yes

schema-free

Typing

predefined data types such as float or date

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

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

.NET Client API
HTTP API
LINQ

.Net

HTTP API
Jupyter
WebSocket

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
Python

.Net
Basic
C
Java
Objective C
PHP
Python

.Net

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

yes

Domain Events

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

horizontal partitioning

client side managed; servers are not synchronized

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

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

Access rights can be defined down to the item level

Role based authorization

Based on Windows Authentication

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google expands BigQuery with Gemini, brings vector support to cloud databases
29 February 2024, VentureBeat

What is Google Bigtable? | Definition from TechTarget
1 March 2022, TechTarget

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

Star Trek: 5 Things Picard Does Better Than Discovery (& 5 Things Discovery Does Better)
4 April 2020, Screen Rant

Launched Just A Year Ago, Open-Source Scality S3 Server Gains Extraordinary Momentum As It Simplifies The Life Of ...
28 June 2017, PR Newswire UK

Time Series Intelligence Software Market Business Insights, Key Trend Analysis | Google, SAP, Azure Time Series ...
24 April 2024, Amoré

provided by Google News

Share this page