DBMS > Heroic vs. LevelDB vs. PostGIS vs. UniData,UniVerse

System Properties Comparison Heroic vs. LevelDB vs. PostGIS vs. UniData,UniVerse

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Editorial information provided by DB-Engines

Name

Description

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Spatial extension of PostgreSQL

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Secondary database models

Relational DBMS

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

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	20.16
Rank	#29	Overall
	#1	Spatial DBMS

Score	2.25
Rank	#112	Overall
	#2	Multivalue DBMS

Website

github.com/spotify/heroic

github.com/google/leveldb

postgis.net

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

spotify.github.io/heroic

github.com/google/leveldb/blob/main/doc/index.md

postgis.net/documentation

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Spotify

Google

Rocket Software

Initial release

2014

2011

2005

1985

Current release

1.23, February 2021

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

Open Source

GPL v2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

C++

Server operating systems

Illumos
Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

via Elasticsearch

yes

SQL

Support of SQL

yes

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

based on PostgreSQL

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

based on PostgreSQL

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

In-memory capabilities

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

User concepts

Access control

yes

based on PostgreSQL

Access rights according to SQL-standard and operating system based

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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