DBMS > H2GIS vs. NSDb vs. Ultipa vs. Yaacomo

System Properties Comparison H2GIS vs. NSDb vs. Ultipa vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Spatial extension of H2

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

High performance Graph DBMS supporting HTAP high availability cluster deployment

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Secondary database models

Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.13
Rank	#335	Overall
	#31	Graph DBMS

Website

www.h2gis.org

nsdb.io

www.ultipa.com

yaacomo.com

Technical documentation

www.h2gis.org/docs/home

nsdb.io/Architecture

www.ultipa.com/document

Developer

CNRS

Ultipa

Q2WEB GmbH

Initial release

2013

2017

2019

2009

License

Commercial or Open Source

Open Source

LGPL 3.0

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, Scala

Server operating systems

Linux
macOS

Android
Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, 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.

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

gRPC
HTTP REST
WebSocket

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Java

Java
Scala

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

based on H2

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

Source-replica replication

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

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

In-memory capabilities

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

yes

User concepts

Access control

yes

based on H2

fine grained access rights according to SQL-standard

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7 March 2024, Caj News Africa

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