DBMS > Apache IoTDB vs. etcd vs. SAP HANA vs. WakandaDB

System Properties Comparison Apache IoTDB vs. etcd vs. SAP HANA vs. WakandaDB

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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

In-memory, column based data store. Available as appliance or cloud service

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial 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	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

iotdb.apache.org

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

www.sap.com/products/hana.html

wakanda.github.io

Technical documentation

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

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

help.sap.com/hana

wakanda.github.io/doc

Developer

Apache Software Foundation

SAP

Wakanda SAS

Initial release

2018

2010

2012

Current release

1.1.0, April 2023

3.4, August 2019

2.0 SPS07 (April 4, 2023), April 2023

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++, JavaScript

Server operating systems

All OS with a Java VM (>= 1.8)

FreeBSD
Linux
Windows

experimental

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

yes

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

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

gRPC
JSON over HTTP

JDBC
ODBC

RESTful HTTP API

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

JavaScript

Server-side scripts

Stored procedures

yes

SQLScript, R

yes

Triggers

yes

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

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

yes

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.

yes

none

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

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

User concepts

Access control

yes

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