DBMS > Derby vs. Google Cloud Firestore vs. H2 vs. Microsoft SQL Server vs. VoltDB

System Properties Comparison Derby vs. Google Cloud Firestore vs. H2 vs. Microsoft SQL Server vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

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

Microsofts flagship relational DBMS

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

db.apache.org/derby

firebase.google.com/products/firestore

www.h2database.com

www.microsoft.com/en-us/sql-server

www.voltdb.com

Technical documentation

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

firebase.google.com/docs/firestore

www.h2database.com/html/main.html

learn.microsoft.com/en-US/sql/sql-server

docs.voltdb.com

Developer

Apache Software Foundation

Google

Thomas Mueller

Microsoft

VoltDB Inc.

Initial release

1997

2017

2005

1989

2010

Current release

10.17.1.0, November 2023

2.2.220, July 2023

SQL Server 2022, November 2022

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

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

commercial

restricted free version is available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Java, C++

Server operating systems

All OS with a Java VM

hosted

All OS with a Java VM

Linux
Windows

Linux
OS X

for development

Data scheme

yes

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

yes

only a subset of SQL 99

APIs and other access methods

JDBC

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Java

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

Java

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes, Firebase Rules & Cloud Functions

Java Stored Procedures and User-Defined Functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Java

Triggers

yes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

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

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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