DBMS > Apache Drill vs. Datomic vs. Greenplum vs. Machbase Neo

System Properties Comparison Apache Drill vs. Datomic vs. Greenplum 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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

TimeSeries DBMS for AIoT and BigData

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Website

Technical documentation

drill.apache.org/docs

docs.datomic.com

docs.greenplum.org

machbase.com/dbms

Developer

Apache Software Foundation

Cognitect

Pivotal Software Inc.

Machbase

Initial release

2012

2005

2013

Current release

1.20.3, January 2023

1.0.6735, June 2023

7.0.0, September 2023

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

limited edition free

Open Source

Apache 2.0

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

Java, Clojure

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux

Linux
macOS
Windows

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.

yes

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC

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

Supported programming languages

C++

Clojure
Java

C
Java
Perl
Python
R

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

user defined functions

yes

Transaction Functions

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

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

none

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

Depending on the underlying data source

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

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

recommended only for testing and development

yes

volatile and lookup table

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

simple password-based access control

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More resources

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