DBMS > Databend vs. Datomic vs. Microsoft Azure AI Search vs. SAP HANA

System Properties Comparison Databend vs. Datomic vs. Microsoft Azure AI Search vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Search-as-a-service for web and mobile app development

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

Primary database model

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Vector DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

github.com/datafuselabs/databend
www.databend.com

www.datomic.com

azure.microsoft.com/en-us/services/search

www.sap.com/products/hana.html

Technical documentation

docs.databend.com

docs.datomic.com

learn.microsoft.com/en-us/azure/search

help.sap.com/hana

Developer

Databend Labs

Cognitect

Microsoft

SAP

Initial release

2021

2012

2015

2010

Current release

1.0.59, April 2023

1.0.7075, December 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

limited edition free

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

Rust

Java, Clojure

Server operating systems

hosted
Linux
macOS

All OS with a Java VM

hosted

Appliance or cloud-service

Data scheme

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

yes

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

Clojure
Java

C#
Java
JavaScript
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

SQLScript, R

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

Implicit feature of the cloud service

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles

yes

using Azure authentication

yes

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