DBMS > Derby vs. Ehcache vs. Google Cloud Firestore vs. Hypertable vs. Snowflake

System Properties Comparison Derby vs. Ehcache vs. Google Cloud Firestore vs. Hypertable vs. Snowflake

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

A widely adopted Java cache with tiered storage options

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.

An open source BigTable implementation based on distributed file systems such as Hadoop

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

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

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

db.apache.org/derby

www.ehcache.org

firebase.google.com/products/firestore

www.snowflake.com

Technical documentation

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

www.ehcache.org/documentation

firebase.google.com/docs/firestore

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Terracotta Inc, owned by Software AG

Google

Hypertable Inc.

Snowflake Computing Inc.

Initial release

1997

2009

2017

2009

2014

Current release

10.17.1.0, November 2023

3.10.0, March 2022

0.9.8.11, March 2016

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

GNU version 3. Commercial license available

commercial

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

All OS with a Java VM

hosted

Linux
OS X
Windows

an inofficial Windows port is available

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

APIs and other access methods

JDBC

JCache

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

C++ API
Thrift

CLI Client
JDBC
ODBC

Supported programming languages

Java

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

C++
Java
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes, Firebase Rules & Cloud Functions

user defined functions

Triggers

yes

Cache Event Listeners

yes, with Cloud Functions

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

by using Terracotta Server

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

by using Terracotta Server

Multi-source replication

selectable replication factor on file system level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

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.

Users with fine-grained authorization concept, user roles and pluggable authentication

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