DBMS > H2GIS vs. Riak KV vs. Sadas Engine vs. Typesense vs. XTDB

System Properties Comparison H2GIS vs. Riak KV vs. Sadas Engine vs. Typesense vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

Distributed, fault tolerant key-value store

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Spatial DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

Search engine

Document store

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	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.79
Rank	#210	Overall
	#14	Search engines

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.h2gis.org

www.sadasengine.com

typesense.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.h2gis.org/docs/home

www.tiot.jp/riak-docs/riak/kv/latest

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

typesense.org/docs

www.xtdb.com/docs

Developer

CNRS

OpenSource, formerly Basho Technologies

SADAS s.r.l.

Juxt Ltd.

Initial release

2013

2009

2006

2015

2019

Current release

3.2.0, December 2022

8.0

1.19, September 2021

License

Commercial or Open Source

Open Source

LGPL 3.0

Open Source

Apache version 2, commercial enterprise edition

commercial

free trial version available

Open Source

GPL V3

Open Source

MIT License

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

Erlang

C++

Clojure

Server operating systems

Linux
OS X

AIX
Linux
Windows

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

schema-free

pre-defined schema optional

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

restricted

yes

SQL

Support of SQL

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP API
Native Erlang Interface

JDBC
ODBC
Proprietary protocol

RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
C
C#
C++
Groovy
Java
PHP
Python

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Clojure
Java

Server-side scripts

Stored procedures

yes

based on H2

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

no "single point of failure"

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

selectable replication factor

none

Multi-source replication using RAFT

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

yes

based on H2

yes, using Riak Security

Access rights for users, groups and roles according to SQL-standard

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