DBMS > Apache Pinot vs. Coveo vs. SAP HANA vs. Tigris

System Properties Comparison Apache Pinot vs. Coveo vs. SAP HANA vs. Tigris

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Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

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

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

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

Relational DBMS

Search engine

Relational DBMS

Document store
Key-value store
Search engine
Time Series 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	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	2.28
Rank	#114	Overall
	#11	Search engines

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	0.02
Rank	#369	Overall
	#51	Document stores
	#55	Key-value stores
	#24	Search engines
	#38	Time Series DBMS

Website

pinot.apache.org

www.coveo.com

www.sap.com/products/hana.html

www.tigrisdata.com

Technical documentation

docs.pinot.apache.org

docs.coveo.com

help.sap.com/hana

www.tigrisdata.com/docs

Developer

Apache Software Foundation and contributors

Coveo

SAP

Tigris Data, Inc.

Initial release

2015

2012

2010

2022

Current release

1.0.0, September 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

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

All OS with a Java JDK11 or higher

hosted

Appliance or cloud-service

Linux
macOS
Windows

Data scheme

yes

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

SQL-like query language

yes

APIs and other access methods

JDBC

RESTful HTTP API

JDBC
ODBC

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

Go
Java
Python

C#
Java
JavaScript
Python

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using FoundationDB

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

yes

Access rights for users and roles

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