DBMS > Apache Drill vs. Google BigQuery vs. Greenplum vs. H2 vs. Machbase Neo

System Properties Comparison Apache Drill vs. Google BigQuery vs. Greenplum vs. H2 vs. Machbase Neo

Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

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.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Spatial DBMS

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

Score	2.28
Rank	#119	Overall
	#23	Document stores
	#56	Relational DBMS

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	9.23
Rank	#47	Overall
	#30	Relational DBMS

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	0.22
Rank	#324	Overall
	#29	Time Series DBMS

Website

drill.apache.org

cloud.google.com/bigquery

greenplum.org

www.h2database.com

machbase.com

Technical documentation

drill.apache.org/docs

cloud.google.com/bigquery/docs

docs.greenplum.org

www.h2database.com/html/main.html

machbase.com/dbms

Developer

Apache Software Foundation

Google

Pivotal Software Inc.

Thomas Mueller

Machbase

Initial release

2012

2010

2005

2013

Current release

1.20.3, January 2023

7.0.0, September 2023

2.2.220, July 2023

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

free test version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Windows

hosted

Linux

All OS with a Java VM

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/JSON API

JDBC
ODBC

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

Supported programming languages

C++

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
Java
Perl
Python
R

Java

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

simple password-based access control

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