DBMS > Datomic vs. Hyprcubd vs. Microsoft Azure AI Search vs. PostGIS vs. SwayDB

System Properties Comparison Datomic vs. Hyprcubd vs. Microsoft Azure AI Search vs. PostGIS vs. SwayDB

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

Serverless Time Series DBMS

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

Spatial extension of PostgreSQL

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Secondary database models

Vector DBMS

Relational DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	5.52
Rank	#59	Overall
	#6	Search engines

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Website

www.datomic.com

hyprcubd.com (offline)

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

postgis.net

swaydb.simer.au

Technical documentation

docs.datomic.com

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

postgis.net/documentation

Developer

Cognitect

Hyprcubd, Inc.

Microsoft

Simer Plaha

Initial release

2012

2015

2005

2018

Current release

1.0.7075, December 2023

3.4.2, February 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

GPL v2.0

Open Source

GNU Affero GPL V3.0

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

Java, Clojure

Scala

Server operating systems

All OS with a Java VM

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

gRPC (https)

RESTful HTTP API

Supported programming languages

Clojure
Java

C#
Java
JavaScript
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

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

based on PostgreSQL

none

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

based on PostgreSQL

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Atomic execution of operations

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

token access

yes

using Azure authentication

yes

based on PostgreSQL

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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