DBMS > Apache Doris vs. Drizzle vs. EsgynDB vs. Sequoiadb vs. Sqrrl

System Properties Comparison Apache Doris vs. Drizzle vs. EsgynDB vs. Sequoiadb vs. Sqrrl

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.

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

An MPP-based analytics DBMS embracing the MySQL protocol

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

NewSQL database with distributed OLTP and SQL

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Relational DBMS

Document store
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

www.esgyn.cn

www.sequoiadb.com

sqrrl.com

Technical documentation

github.com/apache/doris/wiki

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Apache Software Foundation, originally contributed from Baidu

Drizzle project, originally started by Brian Aker

Esgyn

Sequoiadb Ltd.

Amazon

originally Sqrrl Data, Inc.

Initial release

2017

2008

2015

2013

2012

Current release

1.2.2, February 2023

7.2.4, September 2012

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GNU GPL

commercial

Open Source

Server: AGPL; Client: Apache V2

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

Java

C++

C++, Java

C++

Java

Server operating systems

Linux

FreeBSD
Linux
OS X

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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
MySQL client

JDBC

ADO.NET
JDBC
ODBC

proprietary protocol using JSON

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

Java

C
C++
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

.Net
C++
Java
PHP
Python

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

JavaScript

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Multi-source replication between multi datacenters

Source-replica replication

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Document is locked during a transaction

Atomic updates per row, document, or graph entity

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.

User concepts

Access control

fine grained access rights according to SQL-standard

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

simple password-based access control

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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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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Recent citations in the news

Workload Isolation in Apache Doris: Optimizing Resource Management and Performance
25 May 2024, hackernoon.com

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Mark Terenzoni
23 February 2024, Dark Reading

Amazon's cloud business acquires Sqrrl, a security start-up with NSA roots
23 January 2018, CNBC

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18 September 2023, Mint

provided by Google News

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