DBMS > Apache Impala vs. OpenSearch vs. Yanza

System Properties Comparison Apache Impala vs. OpenSearch vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

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

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Search engine

Time Series DBMS

Secondary database models

Document store

Vector DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	16.36
Rank	#37	Overall
	#4	Search engines

Website

impala.apache.org

github.com/opensearch-project
opensearch.org

yanza.com

Technical documentation

impala.apache.org/impala-docs.html

opensearch.org/docs/latest

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Amazon Web Services

Yanza

Initial release

2013

2021

2015

Current release

4.1.0, June 2022

2.5.0, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

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++

Java

Server operating systems

Linux

All OS with a Java VM

Windows

Data scheme

yes

schema-free

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

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

All search fields are automatically indexed

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP/JSON API

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

by using the 'percolation' feature

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

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

Transaction concepts

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

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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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