DBMS > Apache Druid vs. Coveo vs. Microsoft Azure Table Storage vs. SAP HANA

System Properties Comparison Apache Druid vs. Coveo vs. Microsoft Azure Table Storage vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

A Wide Column Store for rapid development using massive semi-structured datasets

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Relational DBMS
Time Series DBMS

Search engine

Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	2.11
Rank	#118	Overall
	#11	Search engines

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

druid.apache.org

www.coveo.com

azure.microsoft.com/en-us/services/storage/tables

www.sap.com/products/hana.html

Technical documentation

druid.apache.org/docs/latest/design

docs.coveo.com

help.sap.com/hana

Developer

Apache Software Foundation and contributors

Coveo

Microsoft

SAP

Initial release

2012

2010

Current release

29.0.1, April 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

Linux
OS X
Unix

hosted

Appliance or cloud-service

Data scheme

yes

schema-less columns are supported

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 for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
Java
JavaScript
Python

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

Server-side scripts

Stored procedures

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

yes

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

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

optimistic locking

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

granular access controls, API key management, content filters

Access rights based on private key authentication or shared access signatures

yes

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