DBMS > Apache IoTDB vs. GeoMesa vs. Kinetica vs. OpenSearch vs. OrientDB

System Properties Comparison Apache IoTDB vs. GeoMesa vs. Kinetica vs. OpenSearch vs. OrientDB

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Fully vectorized database across both GPUs and CPUs

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

Multi-model DBMS (Document, Graph, Key/Value)

Primary database model

Document store
Graph DBMS
Key-value store

Secondary database models

Spatial DBMS
Time Series DBMS

Vector DBMS

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Website

iotdb.apache.org

www.geomesa.org

www.kinetica.com

github.com/opensearch-project
opensearch.org

orientdb.org

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

www.geomesa.org/documentation/stable/user/index.html

docs.kinetica.com

opensearch.org/docs/latest

www.orientdb.com/docs/last/index.html

Developer

Apache Software Foundation

CCRi and others

Kinetica

Amazon Web Services

OrientDB LTD; CallidusCloud; SAP

Initial release

2018

2014

2012

2021

2010

Current release

1.1.0, April 2023

5.0.0, May 2024

7.1, August 2021

2.5.0, January 2023

3.2.29, March 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

commercial

Open Source

Apache Version 2.0

Open Source

Apache version 2

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.

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Implementation language

Java

Scala

C, C++

Java

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

All OS with a Java VM

All OS with a Java JDK (>= JDK 6)

Data scheme

yes

schema-free

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

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

SQL-like query language

SQL-like query language, no joins

APIs and other access methods

JDBC
Native API

JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP/JSON API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C++
Java
JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

user defined functions

yes

Java, Javascript

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

by using the 'percolation' feature

Hooks

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

depending on storage layer

Source-replica replication

yes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

depending on storage layer

Immediate Consistency or Eventual Consistency depending on configuration

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

relationship in graphs

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

In-memory capabilities

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

yes

depending on storage layer

yes

GPU vRAM or System RAM

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users and roles on table level

Access rights for users and roles; record level security configurable

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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