DBMS > Apache IoTDB vs. Heroic vs. SAP IQ vs. WakandaDB

System Properties Comparison Apache IoTDB vs. Heroic vs. SAP IQ 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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Columnar RDBMS optimized for Big Data analytics

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

Primary database model

Time Series DBMS

Relational DBMS

column-oriented

Object oriented DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

iotdb.apache.org

github.com/spotify/heroic

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

wakanda.github.io

Technical documentation

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

spotify.github.io/heroic

help.sap.com/docs/SAP_IQ

wakanda.github.io/doc

Developer

Apache Software Foundation

Spotify

SAP, formerly Sybase

Wakanda SAS

Initial release

2018

2014

1994

2012

Current release

1.1.0, April 2023

16.1 SPS04, April 2019

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Open Source

AGPLv3, extended commercial license available

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

C++, JavaScript

Server operating systems

All OS with a Java VM (>= 1.8)

AIX
HP-UX
Linux
Solaris
Windows

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

via Elasticsearch

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
JDBC
ODBC
RESTful HTTP API

RESTful HTTP API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C
C#
C++
Java
Perl
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

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

yes

SAP/Sybase Replication Server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency
Immediate Consistency

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

fine grained access rights according to SQL-standard

yes

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