DBMS > OrigoDB vs. Spark SQL vs. SpatiaLite vs. YDB

System Properties Comparison OrigoDB vs. Spark SQL vs. SpatiaLite vs. YDB

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Editorial information provided by DB-Engines

Name

Description

A fully ACID in-memory object graph database

Spark SQL is a component on top of 'Spark Core' for structured data processing

Spatial extension of SQLite

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Document store
Object oriented DBMS

Relational DBMS

Spatial DBMS

Document store
Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Score	0.35
Rank	#278	Overall
	#43	Document stores
	#127	Relational DBMS

Website

origodb.com

spark.apache.org/sql

www.gaia-gis.it/fossil/libspatialite/index

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

origodb.com/docs

spark.apache.org/docs/latest/sql-programming-guide.html

www.gaia-gis.it/gaia-sins/spatialite_topics.html

ydb.tech/en/docs

Developer

Robert Friberg et al

Apache Software Foundation

Alessandro Furieri

Yandex

Initial release

2009

under the name LiveDB

2014

2008

2019

Current release

3.5.0 ( 2.13), September 2023

5.0.0, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Open Source

Apache 2.0; commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

C++

Server operating systems

Linux
Windows

Linux
OS X
Windows

server-less

Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language (YQL)

APIs and other access methods

.NET Client API
HTTP API
LINQ

JDBC
ODBC

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

.Net

Java
Python
R
Scala

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

client side managed; servers are not synchronized

yes, utilizing Spark Core

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Active-passive shard replication

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

depending on model

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

Write ahead log

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

Role based authorization

Access rights defined for Yandex Cloud users

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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