DBMS > Drizzle vs. EXASOL vs. Google Cloud Bigtable vs. SWC-DB

System Properties Comparison Drizzle vs. EXASOL vs. Google Cloud Bigtable vs. SWC-DB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Key-value store
Wide column store

Wide column store

Secondary database models

Time Series DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

www.exasol.com

cloud.google.com/bigtable

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

www.exasol.com/resources

cloud.google.com/bigtable/docs

Developer

Drizzle project, originally started by Brian Aker

Exasol

Google

Alex Kashirin

Initial release

2008

2000

2015

2020

Current release

7.2.4, September 2012

0.5, April 2021

License

Commercial or Open Source

Open Source

GNU GPL

commercial

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

C++

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like query language

APIs and other access methods

JDBC

.Net
JDBC
ODBC
WebSocket

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

Proprietary protocol
Thrift

Supported programming languages

C
C++
Java
PHP

Java
Lua
Python
R

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

C++

Server-side scripts

Stored procedures

user defined functions

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

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.

yes

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles according to SQL-standard

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

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

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

show all

Recent citations in the news

It's Back to the Database Future for Exasol CEO Tewes
26 October 2023, Datanami

Mathias Golombek, Chief Technology Officer of Exasol – Interview Series
21 May 2024, Unite.AI

Exasol Finds AI Underinvestment Leads to Business Failure, But Data Challenges Stall Rapid Adoption
14 May 2024, insideBIGDATA

Exasol gets jolt of AI with Espresso suite of capabilities
26 February 2024, TechTarget

Exasol Unveils New Suite of AI Tools to Turbocharge Enterprise Data Analytics
21 February 2024, Business Wire

provided by Google News

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

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

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

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

provided by Google News

2022 All O-Zone Football Team
17 December 2022, Ozarks Sports Zone

provided by Google News

Share this page