DBMS > Oracle Rdb vs. Sadas Engine vs. Vertica vs. YDB

System Properties Comparison Oracle Rdb vs. Sadas Engine vs. Vertica vs. YDB

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Editorial information provided by DB-Engines

Name

Description

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

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

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

Relational DBMS

Column oriented

Document store
Relational DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Score	0.39
Rank	#269	Overall
	#43	Document stores
	#126	Relational DBMS

Website

www.oracle.com/database/technologies/related/rdb.html

www.sadasengine.com

www.vertica.com

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

Technical documentation

www.oracle.com/database/technologies/related/rdb-doc.html

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

vertica.com/documentation

ydb.tech/en/docs

Developer

Oracle, originally developed by Digital Equipment Corporation (DEC)

SADAS s.r.l.

OpenText

previously Micro Focus and Hewlett Packard

Yandex

Initial release

1984

2006

2005

2019

Current release

7.4.1.1, 2021

8.0

12.0.3, January 2023

License

Commercial or Open Source

commercial

free trial version available

commercial

Limited community edition free

Open Source

Apache 2.0; commercial license available

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

HP Open VMS

AIX
Linux
Windows

Linux

Data scheme

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

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

Typing

predefined data types such as float or date

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

yes

SQL

Support of SQL

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

SQL-like query language (YQL)

APIs and other access methods

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

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

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

horizontal partitioning, hierarchical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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'

User concepts

Access control

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

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

Access rights defined for Yandex Cloud users

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