DBMS > Ehcache vs. GeoSpock vs. Microsoft Azure AI Search vs. Snowflake

System Properties Comparison Ehcache vs. GeoSpock vs. Microsoft Azure AI Search vs. Snowflake

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Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

A widely adopted Java cache with tiered storage options

Spatial and temporal data processing engine for extreme data scale

Search-as-a-service for web and mobile app development

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

Primary database model

Secondary database models

Time Series DBMS

Vector DBMS

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

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.ehcache.org

geospock.com

azure.microsoft.com/en-us/services/search

www.snowflake.com

Technical documentation

www.ehcache.org/documentation

learn.microsoft.com/en-us/azure/search

docs.snowflake.net/manuals/index.html

Developer

Terracotta Inc, owned by Software AG

GeoSpock

Microsoft

Snowflake Computing Inc.

Initial release

2009

2015

2014

Current release

3.10.0, March 2022

2.0, September 2019

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

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Implementation language

Java

Java, Javascript

Server operating systems

All OS with a Java VM

hosted

Data scheme

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

JCache

JDBC

RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

Java

C#
Java
JavaScript
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Cache Event Listeners

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Automatic sharding

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

Implicit feature of the cloud service

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

supports JTA and can work as an XA resource

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 can be defined per table

yes

using Azure authentication

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

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