DBMS > atoti vs. Coveo vs. Ehcache vs. Google BigQuery

System Properties Comparison atoti vs. Coveo vs. Ehcache vs. Google BigQuery

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

A widely adopted Java cache with tiered storage options

Large scale data warehouse service with append-only tables

Primary database model

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Score	2.11
Rank	#118	Overall
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Score	4.64
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	#8	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Website

atoti.io

www.coveo.com

www.ehcache.org

cloud.google.com/bigquery

Technical documentation

docs.atoti.io

docs.coveo.com

www.ehcache.org/documentation

cloud.google.com/bigquery/docs

Developer

ActiveViam

Coveo

Terracotta Inc, owned by Software AG

Google

Initial release

2012

2009

2010

Current release

3.10.0, March 2022

License

Commercial or Open Source

commercial

free versions available

commercial

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

Server operating systems

hosted

All OS with a Java VM

hosted

Data scheme

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

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.

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

yes

APIs and other access methods

RESTful HTTP API

JCache

RESTful HTTP/JSON API

Supported programming languages

C#
Java
JavaScript
Python

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

Python

user defined functions

in JavaScript

Triggers

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

yes

Sharding

by using Terracotta Server

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

supports JTA and can work as an XA resource

Since BigQuery is designed for querying data

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

granular access controls, API key management, content filters

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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