DBMS > Altibase vs. GridDB vs. InterSystems IRIS vs. OpenSearch vs. Vertica

System Properties Comparison Altibase vs. GridDB vs. InterSystems IRIS vs. OpenSearch vs. Vertica

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Scalable in-memory time series database optimized for IoT and Big Data

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

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

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

Relational DBMS

Time Series DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Search engine

Relational DBMS

Column oriented

Secondary database models

Key-value store
Relational DBMS

Vector DBMS

Spatial DBMS
Time Series DBMS

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	3.54
Rank	#84	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

altibase.com

griddb.net

www.intersystems.com/products/intersystems-iris

github.com/opensearch-project
opensearch.org

www.vertica.com

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.griddb.net

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

opensearch.org/docs/latest

vertica.com/documentation

Developer

Altibase

Toshiba Corporation

InterSystems

Amazon Web Services

OpenText

previously Micro Focus and Hewlett Packard

Initial release

1999

2013

2018

2021

2005

Current release

v7.3, 2023, August 2023

5.1, August 2022

2023.3, June 2023

2.5.0, January 2023

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

Open Source

Apache Version 2.0

commercial

Limited community edition free

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.

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Implementation language

C++

Java

C++

Server operating systems

AIX
HP-UX
Linux

Linux

AIX
Linux
macOS
Ubuntu
Windows

All OS with a Java VM

Linux

Data scheme

yes

depending on used data model

schema-free

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

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

numerical, string, blob, geometry, boolean, timestamp

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

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

SQL

Support of SQL

ANSI SQL-92

SQL92, SQL-like TQL (Toshiba Query Language)

yes

SQL-like query language

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

APIs and other access methods

JDBC
ODBC
Proprietary protocol

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP/JSON API

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

character-based, interactive, front-end utility

Supported programming languages

C
C++
Java

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

.Net
C++
Java
JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

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

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

by using the 'percolation' feature

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

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

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

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

ACID

ACID at container level

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

yes

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

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
» more

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

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

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

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

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

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Market metrics

GitHub trending repository
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Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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

Cost-based models and subscription-based models are both available. One license is...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.