DBMS > Google Cloud Bigtable vs. Quasardb vs. TimesTen vs. VelocityDB

System Properties Comparison Google Cloud Bigtable vs. Quasardb vs. TimesTen vs. VelocityDB

Please select another system to include it in the comparison.

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.

Distributed, high-performance timeseries database

In-Memory RDBMS compatible to Oracle

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

Primary database model

Key-value store
Wide column store

Time Series DBMS

Relational DBMS

Graph DBMS
Object oriented 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	0.19
Rank	#327	Overall
	#30	Time Series DBMS

Score	1.35
Rank	#165	Overall
	#75	Relational DBMS

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

Website

cloud.google.com/bigtable

quasar.ai

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

velocitydb.com

Technical documentation

cloud.google.com/bigtable/docs

doc.quasar.ai/master

docs.oracle.com/database/timesten-18.1

velocitydb.com/UserGuide

Developer

Google

quasardb

Oracle, TimesTen Performance Software, HP

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

VelocityDB Inc

Initial release

2015

2009

1998

2011

Current release

3.14.1, January 2024

11 Release 2 (11.2.2.8.0)

7.x

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

C++

Server operating systems

hosted

BSD
Linux
OS X
Windows

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

Any that supports .NET

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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.

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

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

HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

.Net

Supported programming languages

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

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

C
C++
Java
PL/SQL

.Net

Server-side scripts

Stored procedures

PL/SQL

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication with selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

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

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

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

by using LevelDB

yes

by means of logfiles and checkpoints

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

User concepts

Access control

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

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

Based on Windows Authentication

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

Quasar Partners with PTC for IoT Data Solutions
11 September 2023, Read IT Quik

Record quasar is most luminous object in the universe
20 February 2024, EarthSky

Quasar Partners with PTC to Empower IoT Customers with High-Performance Data Solutions
11 September 2023, Datanami

Quasar Selected by National Renewable Energy Laboratory to Help with Energy System De-risking and Optimization
6 June 2023, PR Newswire

QUASAR yacht (Bilgin, 46.8m, 2016)
3 July 2023, Boat International

provided by Google News

In-memory databases with Emulex Gen 7
25 October 2023, Broadcom Inc.

provided by Google News

Share this page