DBMS > Apache IoTDB vs. GeoMesa vs. OrientDB vs. Riak KV vs. SAP IQ

System Properties Comparison Apache IoTDB vs. GeoMesa vs. OrientDB vs. Riak KV vs. SAP IQ

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.

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

Distributed, fault tolerant key-value store

Columnar RDBMS optimized for Big Data analytics

Primary database model

Time Series DBMS

Spatial DBMS

Document store
Graph DBMS
Key-value store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Relational DBMS

column-oriented

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Website

iotdb.apache.org

www.geomesa.org

orientdb.org

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

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

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

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

www.tiot.jp/riak-docs/riak/kv/latest

help.sap.com/docs/SAP_IQ

Developer

Apache Software Foundation

CCRi and others

OrientDB LTD; CallidusCloud; SAP

OpenSource, formerly Basho Technologies

SAP, formerly Sybase

Initial release

2018

2014

2010

2009

1994

Current release

1.1.0, April 2023

4.0.5, February 2024

3.2.29, March 2024

3.2.0, December 2022

16.1 SPS04, April 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

Apache version 2

Open Source

Apache version 2, commercial enterprise edition

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.

Implementation language

Java

Scala

Java

Erlang

Server operating systems

All OS with a Java VM (>= 1.8)

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

Linux
OS X

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

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

schema-free

yes

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

restricted

yes

SQL

Support of SQL

SQL-like query language

SQL-like query language, no joins

yes

APIs and other access methods

JDBC
Native API

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

HTTP API
Native Erlang Interface

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Java, Javascript

Erlang

yes

Triggers

yes

Hooks

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

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

depending on storage layer

Sharding

no "single point of failure"

shared disk or shared nothing architectures with SAP IQ Multiplexer

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

Multi-source replication

selectable replication factor

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

could be achieved with distributed queries

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

depending on storage layer

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

links between data sets can be stored

yes

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

User concepts

Access control

yes

depending on the DBMS used for storage

Access rights for users and roles; record level security configurable

yes, using Riak Security

fine grained access rights according to SQL-standard

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