DBMS > Apache Drill vs. Citus vs. Galaxybase vs. Machbase Neo

System Properties Comparison Apache Drill vs. Citus vs. Galaxybase vs. Machbase Neo

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Scalable, ACID-compliant native distributed parallel graph platform

TimeSeries DBMS for AIoT and BigData

Primary database model

Document store
Relational DBMS

Relational DBMS

Graph DBMS

Time Series DBMS

Secondary database models

Document store

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	0.07
Rank	#377	Overall
	#40	Graph DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Website

Technical documentation

drill.apache.org/docs

docs.citusdata.com

machbase.com/dbms

Developer

Apache Software Foundation

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Machbase

Initial release

2012

2010

2017

2013

Current release

1.20.3, January 2023

8.1, December 2018

Nov 20, November 2021

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

AGPL, commercial license also available

commercial

free test version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and Java

Server operating systems

Linux
OS X
Windows

Linux

Linux
macOS
Windows

Data scheme

schema-free

yes

Strong typed schema

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.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

standard, with numerous extensions

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Supported programming languages

C++

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Go
Java
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

user defined procedures and functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

volatile and lookup table

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

Role-based access control

simple password-based access control

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