DBMS > Apache Impala vs. Coveo vs. Microsoft Azure Synapse Analytics vs. ToroDB

System Properties Comparison Apache Impala vs. Coveo vs. Microsoft Azure Synapse Analytics vs. ToroDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

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

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Secondary database models

Document store

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

Score	14.03
Rank	#40	Overall
	#24	Relational DBMS

Score	2.34
Rank	#117	Overall
	#11	Search engines

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Website

impala.apache.org

www.coveo.com

azure.microsoft.com/services/synapse-analytics

github.com/torodb/server

Technical documentation

impala.apache.org/impala-docs.html

docs.coveo.com

docs.microsoft.com/azure/synapse-analytics

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Coveo

Microsoft

8Kdata

Initial release

2013

2012

2016

Current release

4.1.0, June 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

AGPL-V3

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

C++

Java

Server operating systems

Linux

hosted

All OS with a Java 7 VM

Data scheme

yes

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

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C#
Java
JavaScript
Python

C#
Java
PHP

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

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

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.

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

granular access controls, API key management, content filters

yes

Access rights for users and roles

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More resources

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