DBMS > Amazon CloudSearch vs. Citus vs. HEAVY.AI vs. OpenSearch vs. OrigoDB

System Properties Comparison Amazon CloudSearch vs. Citus vs. HEAVY.AI vs. OpenSearch vs. OrigoDB

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

A fully ACID in-memory object graph database

Primary database model

Search engine

Relational DBMS

Search engine

Document store
Object oriented DBMS

Secondary database models

Document store

Spatial DBMS

Vector DBMS

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Website

aws.amazon.com/cloudsearch

www.citusdata.com

github.com/heavyai/heavydb
www.heavy.ai

github.com/opensearch-project
opensearch.org

origodb.com

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.citusdata.com

docs.heavy.ai

opensearch.org/docs/latest

origodb.com/docs

Developer

Amazon

HEAVY.AI, Inc.

Amazon Web Services

Robert Friberg et al

Initial release

2012

2010

2016

2021

2009

under the name LiveDB

Current release

8.1, December 2018

5.10, January 2022

2.5.0, January 2023

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache Version 2.0

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

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Implementation language

C++ and CUDA

Java

Server operating systems

hosted

Linux

All OS with a Java VM

Linux
Windows

Data scheme

yes

schema-free

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

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

specific XML type available, but no XML query functionality

can be achieved using .NET

Secondary indexes

yes

all search fields are automatically indexed

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

SQL-like query language

APIs and other access methods

HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC
Thrift
Vega

Java API
RESTful HTTP/JSON API

.NET Client API
HTTP API
LINQ

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

All languages supporting JDBC/ODBC/Thrift
Python

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

.Net

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

by using the 'percolation' feature

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

Round robin

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication

yes

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

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

Foreign keys

Referential integrity

yes

depending on model

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

In-memory capabilities

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

yes

User concepts

Access control

authentication via encrypted signatures

fine grained access rights according to SQL-standard

Role based authorization

More information provided by the system vendor

Specific characteristics

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Licensing and pricing models

The OpenSearch Project offers open source software licensed under Apache License...
» more

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