DBMS > OpenSearch vs. Oracle Rdb vs. Snowflake vs. Vertica

System Properties Comparison OpenSearch vs. Oracle Rdb vs. Snowflake vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

Cloud-based data warehousing service for structured and semi-structured data

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.

Primary database model

Search engine

Relational DBMS

Column oriented

Secondary database models

Vector DBMS

Spatial DBMS
Time Series DBMS

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

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

github.com/opensearch-project
opensearch.org

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

www.snowflake.com

www.vertica.com

Technical documentation

opensearch.org/docs/latest

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

docs.snowflake.net/manuals/index.html

vertica.com/documentation

Developer

Amazon Web Services

Oracle, originally developed by Digital Equipment Corporation (DEC)

Snowflake Computing Inc.

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2021

1984

2014

2005

Current release

2.5.0, January 2023

7.4.1.1, 2021

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

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.

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Implementation language

Java

C++

Server operating systems

All OS with a Java VM

HP Open VMS

hosted

Linux

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

yes

support of semi-structured data formats (JSON, XML, Avro)

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

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

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

SQL

Support of SQL

SQL-like query language

yes

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

APIs and other access methods

Java API
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

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

character-based, interactive, front-end utility

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

yes

user defined functions

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

by using the 'percolation' feature

similar concept for controling cloud resources

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

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.

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

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

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
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Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
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Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
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Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
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Cost-based models and subscription-based models are both available. One license is...
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