DBMS > Badger vs. Drizzle vs. Kinetica

System Properties Comparison Badger vs. Drizzle vs. Kinetica

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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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Fully vectorized database across both GPUs and CPUs

Primary database model

Key-value store

Relational DBMS

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

Score	0.12
Rank	#306	Overall
	#46	Key-value stores

Score	0.66
Rank	#212	Overall
	#103	Relational DBMS

Website

github.com/dgraph-io/badger

www.kinetica.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

www.kinetica.com/docs

Developer

DGraph Labs

Drizzle project, originally started by Brian Aker

Kinetica

Initial release

2017

2008

2012

Current release

7.2.4, September 2012

7.1, August 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GNU GPL

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C, C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X

Linux

Data scheme

schema-free

yes

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

SQL-like DML and DDL statements

APIs and other access methods

JDBC

JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
C++
Java
PHP

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

hooks for callbacks inside the server can be used.

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

GPU vRAM or System RAM

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users and roles on table level

More information provided by the system vendor

Specific characteristics

Native and fully vectorized database across both GPUs and CPUs, with memory first...
» more

Competitive advantages

Best in class geospatial and temporal analytics. Lockless architecture provides real-time...
» more

Typical application scenarios

Any application requiring (1) real time insights, (2) time series analysis (3) geospatial...
» more

Key customers

Citibank, US Air Force, Softbank, OVO, Telkomsel, USPS, 2 of the top 3 US Telcos,...
» more

Market metrics

The largest IoT deployment in the world, NORAD, runs on Kinetica.
» more

Licensing and pricing models

Always Free Tier in the Cloud, Pay-As-You-Go Consumption Based Pricing, and Portable...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

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

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1 July 2013, Matthias Gelbmann

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Recent citations in the news

Dgraph raises $11.5 million for scalable graph database solutions
31 July 2019, VentureBeat

provided by Google News

Bank Replaces Hundreds of Spark Streaming Nodes with Kinetica
6 January 2022, Datanami

Kinetica Database Now on Azure
14 October 2021, insideHPC

GPU Database Market 2022 – New Technology Innovation, Global Sales Analysis, Future Expansion, Business Overview, Opportunities Analysis & Demand Forecast to 2025
28 April 2022, Digital Journal

Kinetica Uses GPUs for Advanced In-Database Analytics
24 January 2017, InformationWeek

The insideBIGDATA IMPACT 50 List for Q2 2022
27 April 2022, insideBIGDATA

provided by Google News

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