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

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

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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

Large scale data warehouse service with append-only tables

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Primary database model

Object oriented DBMS

Search engine

Relational DBMS

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

Score	0.61
Rank	#243	Overall
	#11	Object oriented DBMS

Score	2.11
Rank	#118	Overall
	#11	Search engines

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Website

atoti.io

www.coveo.com

cloud.google.com/bigquery

hsqldb.org

Technical documentation

docs.atoti.io

docs.coveo.com

cloud.google.com/bigquery/docs

hsqldb.org/web/hsqlDocsFrame.html

Developer

ActiveViam

Coveo

Google

Initial release

2012

2010

2001

Current release

2.7.2, June 2023

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

based on BSD license

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

Embedded (into Java applications) and Client-Server operating modes

Data scheme

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

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

RESTful HTTP/JSON API

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

C#
Java
JavaScript
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

Python

user defined functions

in JavaScript

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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)

fine grained access rights according to SQL-standard

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