DBMS > Apache Drill vs. Google BigQuery vs. H2 vs. HyperSQL vs. RavenDB

System Properties Comparison Apache Drill vs. Google BigQuery vs. H2 vs. HyperSQL vs. RavenDB

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

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store

Secondary database models

Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.84
Rank	#125	Overall
	#23	Document stores
	#60	Relational DBMS

Score	50.58
Rank	#19	Overall
	#13	Relational DBMS

Score	7.10
Rank	#47	Overall
	#29	Relational DBMS

Score	3.08
Rank	#86	Overall
	#46	Relational DBMS

Score	2.70
Rank	#99	Overall
	#18	Document stores

Website

drill.apache.org

cloud.google.com/bigquery

www.h2database.com

hsqldb.org

ravendb.net

Technical documentation

drill.apache.org/docs

cloud.google.com/bigquery/docs

www.h2database.com/html/main.html

hsqldb.org/web/hsqlDocsFrame.html

ravendb.net/docs

Developer

Apache Software Foundation

Google

Thomas Mueller

Hibernating Rhinos

Initial release

2012

2010

2005

2001

2010

Current release

1.20.3, January 2023

2.2.220, July 2023

2.7.2, June 2023

5.4, July 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

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

Open Source

based on BSD license

Open Source

AGPL version 3, commercial license 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

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
macOS
Raspberry Pi
Windows

Data scheme

schema-free

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

SQL-like query language (RQL)

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

C++

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

All languages supporting JDBC/ODBC
Java

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Java Stored Procedures and User-Defined Functions

Java, SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

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

ACID, Cluster-wide transaction available

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

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

Authorization levels configured per client per database

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