DBMS > Apache Drill vs. Derby vs. Google Cloud Spanner vs. H2 vs. Sadas Engine

System Properties Comparison Apache Drill vs. Derby vs. Google Cloud Spanner vs. H2 vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

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

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

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Document store
Relational DBMS

Relational DBMS

Secondary database models

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	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

drill.apache.org

db.apache.org/derby

cloud.google.com/spanner

www.h2database.com

www.sadasengine.com

Technical documentation

drill.apache.org/docs

db.apache.org/derby/manuals/index.html

cloud.google.com/spanner/docs

www.h2database.com/html/main.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Apache Software Foundation

Google

Thomas Mueller

SADAS s.r.l.

Initial release

2012

1997

2017

2005

2006

Current release

1.20.3, January 2023

10.17.1.0, November 2023

2.2.220, July 2023

8.0

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache version 2

commercial

Open Source

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

commercial

free trial version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

hosted

All OS with a Java VM

AIX
Linux
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

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

Query statements complying to ANSI 2011

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC

JDBC
ODBC
Proprietary protocol

Supported programming languages

C++

Java

Go
Java
JavaScript (Node.js)
Python

Java

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication with 3 replicas for regional instances.

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Strict serializable isolation

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

managed by 'Learn by Usage'

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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