DBMS > Coveo vs. Datastax Enterprise vs. HyperSQL

System Properties Comparison Coveo vs. Datastax Enterprise vs. HyperSQL

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Editorial information provided by DB-Engines

Name

Description

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

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Primary database model

Search engine

Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

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

Score	2.14
Rank	#116	Overall
	#11	Search engines

Score	4.82
Rank	#65	Overall
	#4	Wide column stores

Score	3.14
Rank	#85	Overall
	#46	Relational DBMS

Website

www.coveo.com

www.datastax.com/products/datastax-enterprise

hsqldb.org

Technical documentation

docs.coveo.com

docs.datastax.com

hsqldb.org/web/hsqlDocsFrame.html

Developer

Coveo

DataStax

Initial release

2012

2011

2001

Current release

6.8, April 2020

2.7.2, June 2023

License

Commercial or Open Source

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.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

Implementation language

Java

Server operating systems

hosted

Linux
OS X

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

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

SQL-like DML and DDL statements (CQL); Spark SQL

yes

APIs and other access methods

RESTful HTTP API

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

C#
Java
JavaScript
Python

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware, advanced replication for edge computing

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

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 rights for users can be defined per object

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more

Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
» more

Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
» more

Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more

Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more

Licensing and pricing models

Annual subscription
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

Recent citations in the news

Coveo Announces New Integration with Salesforce Data Cloud
11 September 2024, PR Newswire

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DataStax to launch AI-integrated data platforms HCDP & DSE 6.9
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15 May 2024, Business Wire

DataStax acquires the startup behind low-code AI builder Langflow
4 April 2024, TechCrunch

provided by Google News

HyperSQL DataBase flaw leaves library vulnerable to RCE
24 October 2022, The Daily Swig

Introduction to JDBC with HSQLDB tutorial
14 November 2022, TheServerSide.com

provided by Google News

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