DBMS > Dolt vs. Drizzle vs. FeatureBase vs. Hawkular Metrics

System Properties Comparison Dolt vs. Drizzle vs. FeatureBase vs. Hawkular Metrics

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

A MySQL compatible DBMS with Git-like versioning of data and schema

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

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store

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

Score	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	0.22
Rank	#309	Overall
	#139	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Website

github.com/dolthub/dolt
www.dolthub.com

www.featurebase.com

www.hawkular.org

Technical documentation

docs.dolthub.com

docs.featurebase.com

www.hawkular.org/hawkular-metrics/docs/user-guide

Developer

DoltHub Inc

Drizzle project, originally started by Brian Aker

Molecula and Pilosa Open Source Contributors

Community supported by Red Hat

Initial release

2018

2008

2017

2014

Current release

7.2.4, September 2012

2022, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU GPL

commercial

Open Source

Apache 2.0

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++

Java

Server operating systems

Linux
macOS
Windows

FreeBSD
Linux
OS X

Linux
macOS

Linux
OS X
Windows

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

SQL queries

APIs and other access methods

CLI Client
HTTP REST

JDBC

gRPC
JDBC
Kafka Connector
ODBC

HTTP REST

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Java
PHP

Java
Python

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

currently in alpha release

Triggers

yes

hooks for callbacks inside the server can be used.

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Multi-source replication
Source-replica replication

yes

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

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

Only one user is configurable, and must be specified in the config file at startup

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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

Top Data Version Control Tools for Machine Learning Research in 2023
24 July 2023, MarkTechPost

Dolt, a Relational Database with Git-Like Cloning Features
19 August 2020, The New Stack

Data Versioning at Scale: Chaos and Chaos Management
10 February 2023, InfoQ.com

Radar Trends to Watch: July 2022 – O'Reilly
5 July 2022, oreilly.com

Are you still not using Version Control for Data?
11 April 2020, Towards Data Science

provided by Google News

The 10 Hottest Big Data Startups Of 2021
18 November 2021, CRN

Get Your Infrastructure Ready for Real-Time Analytics
8 March 2022, Built In

32 Data and Analytics Startups That Will Go Big, According to VCs
28 September 2021, Business Insider

The 10 Coolest Big Data Tools Of 2021
7 December 2021, CRN

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

provided by Google News

Share this page