DBMS > EDB Postgres vs. Ehcache vs. Google Cloud Firestore vs. Snowflake vs. TerarkDB

System Properties Comparison EDB Postgres vs. Ehcache vs. Google Cloud Firestore vs. Snowflake vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

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.

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	2.18
Rank	#122	Overall
	#59	Relational DBMS

Score	5.23
Rank	#68	Overall
	#8	Key-value stores

Score	8.96
Rank	#48	Overall
	#8	Document stores

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	0.04
Rank	#377	Overall
	#58	Key-value stores

Website

www.enterprisedb.com

www.ehcache.org

firebase.google.com/products/firestore

www.snowflake.com

github.com/bytedance/terarkdb

Technical documentation

www.enterprisedb.com/docs

www.ehcache.org/documentation

firebase.google.com/docs/firestore

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

EnterpriseDB

Terracotta Inc, owned by Software AG

Google

Snowflake Computing Inc.

ByteDance, originally Terark

Initial release

2005

2009

2017

2014

2016

Current release

14, December 2021

3.10.0, March 2022

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

Open Source

Apache Version 2; commercial licenses available

commercial

restricted open source 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
Windows

All OS with a Java VM

hosted

Data scheme

yes

schema-free

yes

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

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.

yes

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JCache

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

CLI Client
JDBC
ODBC

C++ API
Java API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

Java

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

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

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

horizontal partitioning

by hash, list or range

Sharding

by using Terracotta Server

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

by using Terracotta Server

Multi-source replication

yes

none

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

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, multi-version concurrency control (MVCC)

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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