DBMS > HEAVY.AI vs. IBM Db2 Event Store vs. OpenSearch vs. RDFox

System Properties Comparison HEAVY.AI vs. IBM Db2 Event Store vs. OpenSearch vs. RDFox

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Editorial information provided by DB-Engines

Name

Description

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

Distributed Event Store optimized for Internet of Things use cases

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

High performance knowledge graph and semantic reasoning engine

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Search engine

Graph DBMS
RDF store

Secondary database models

Spatial DBMS

Vector DBMS

Relational DBMS

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	16.36
Rank	#37	Overall
	#4	Search engines

Score	0.23
Rank	#308	Overall
	#25	Graph DBMS
	#14	RDF stores

Website

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

www.ibm.com/products/db2-event-store

github.com/opensearch-project
opensearch.org

www.oxfordsemantic.tech

Technical documentation

docs.heavy.ai

www.ibm.com/docs/en/db2-event-store

opensearch.org/docs/latest

docs.oxfordsemantic.tech

Developer

HEAVY.AI, Inc.

IBM

Amazon Web Services

Oxford Semantic Technologies

Initial release

2016

2017

2021

2017

Current release

5.10, January 2022

2.0

2.5.0, January 2023

6.0, Septermber 2022

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

commercial

free developer edition available

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Aiven for OpenSearch: Fully managed open source search and analytics suite. Out-of-the-box integrations get you up and running in a couple of clicks.

Implementation language

C++ and CUDA

C and C++

Java

C++

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

All OS with a Java VM

Linux
macOS
Windows

Data scheme

yes

schema-free

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

yes

RDF schemas

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

yes

through the embedded Spark runtime

SQL-like query language

APIs and other access methods

JDBC
ODBC
Thrift
Vega

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP/JSON API

RESTful HTTP API
SPARQL 1.1

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

C
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Active-active shard replication

yes

replication via a shared file system

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

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Roles, resources, and access types

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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