DBMS > Apache IoTDB vs. etcd vs. Kinetica vs. OpenSearch vs. SAP SQL Anywhere

System Properties Comparison Apache IoTDB vs. etcd vs. Kinetica vs. OpenSearch vs. SAP SQL Anywhere

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

A distributed reliable key-value store

Fully vectorized database across both GPUs and CPUs

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

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	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	16.03
Rank	#37	Overall
	#4	Search engines

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

iotdb.apache.org

etcd.io
github.com/etcd-io/etcd

www.kinetica.com

github.com/opensearch-project
opensearch.org

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

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

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.kinetica.com

opensearch.org/docs/latest

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Apache Software Foundation

Kinetica

Amazon Web Services

SAP

formerly Sybase

Initial release

2018

2012

2021

1992

Current release

1.1.0, April 2023

3.4, August 2019

7.1, August 2021

2.5.0, January 2023

17, July 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

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.

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Implementation language

Java

C, C++

Java

Server operating systems

All OS with a Java VM (>= 1.8)

FreeBSD
Linux
Windows

experimental

Linux

All OS with a Java VM

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

schema-free

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

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.

yes

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

yes

APIs and other access methods

JDBC
Native API

gRPC
JSON over HTTP

JDBC
ODBC
RESTful HTTP API

Java API
RESTful HTTP/JSON API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C++
Java
JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

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

Server-side scripts

Stored procedures

yes

user defined functions

yes

yes, in C/C++, Java, .Net or Perl

Triggers

yes

yes, watching key changes

yes

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

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

none

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

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Source-replica replication

yes

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

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

GPU vRAM or System RAM

yes

User concepts

Access control

yes

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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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