DBMS > Datomic vs. Firebolt vs. HyperSQL vs. SAP HANA

System Properties Comparison Datomic vs. Firebolt vs. HyperSQL vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

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

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Primary database model

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	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	1.73
Rank	#140	Overall
	#63	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.datomic.com

www.firebolt.io

hsqldb.org

www.sap.com/products/hana.html

Technical documentation

docs.datomic.com

docs.firebolt.io

hsqldb.org/web/hsqlDocsFrame.html

help.sap.com/hana

Developer

Cognitect

Firebolt Analytics Inc.

SAP

Initial release

2012

2020

2001

2010

Current release

1.0.7075, December 2023

2.7.2, June 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

based on BSD license

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Clojure

Java

Server operating systems

All OS with a Java VM

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

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

RESTful HTTP API

.Net
ODBC
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
ODBC

Supported programming languages

Clojure
Java

Go
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

Java, SQL

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

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

depending on storage layer

none

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

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

fine grained access rights according to SQL-standard

yes

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