DBMS > Ehcache vs. Google Cloud Datastore vs. Microsoft Azure Synapse Analytics

System Properties Comparison Ehcache vs. Google Cloud Datastore vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

Key-value store

Document store

Relational DBMS

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

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Website

www.ehcache.org

cloud.google.com/datastore

azure.microsoft.com/services/synapse-analytics

Technical documentation

www.ehcache.org/documentation

cloud.google.com/datastore/docs

docs.microsoft.com/azure/synapse-analytics

Developer

Terracotta Inc, owned by Software AG

Google

Microsoft

Initial release

2009

2008

2016

Current release

3.10.0, March 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses 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

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, details here

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-like query language (GQL)

yes

APIs and other access methods

JCache

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Supported programming languages

Java

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

C#
Java
PHP

Server-side scripts

Stored procedures

using Google App Engine

Transact SQL

Triggers

yes

Cache Event Listeners

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Multi-source replication using Paxos

yes

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

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

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

yes

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