DBMS > Axibase vs. Drizzle vs. FatDB vs. StarRocks

System Properties Comparison Axibase vs. Drizzle vs. FatDB vs. StarRocks

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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.

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Time Series DBMS

Relational DBMS

Document store
Key-value store

Relational DBMS

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

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Website

axibase.com/docs/atsd/finance

www.starrocks.io

Technical documentation

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

Axibase Corporation

Drizzle project, originally started by Brian Aker

FatCloud

The Linux Foundation

since Feb 2023

Initial release

2013

2008

2012

2020

Current release

15585

7.2.4, September 2012

2.5.3, March 2023

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

GNU GPL

commercial

Open Source

Apache Version 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

Java

C++

C++, Java

Server operating systems

Linux

FreeBSD
Linux
OS X

Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

SQL-like query language

yes

with proprietary extensions

Via inetgration in SQL Server

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
MySQL protocol

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C
C++
Java
PHP

Java

Server-side scripts

Stored procedures

yes

via applications

user defined functions

Triggers

yes

hooks for callbacks inside the server can be used.

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

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.

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Can implement custom security layer via applications

Role based access control and fine grained access rights

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More resources

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