DBMS > Apache IoTDB vs. BoltDB vs. SAP HANA vs. SAP SQL Anywhere

System Properties Comparison Apache IoTDB vs. BoltDB vs. SAP HANA vs. SAP SQL Anywhere

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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

An embedded key-value store for Go.

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

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

Primary database model

Time Series DBMS

Key-value store

Relational DBMS

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	#159	Overall
	#14	Time Series DBMS

Score	0.70
Rank	#225	Overall
	#31	Key-value stores

Score	41.32
Rank	#23	Overall
	#16	Relational DBMS

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Website

iotdb.apache.org

github.com/boltdb/bolt

www.sap.com/products/hana.html

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

Technical documentation

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

help.sap.com/hana

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Apache Software Foundation

SAP

formerly Sybase

Initial release

2018

2013

2010

1992

Current release

1.1.0, April 2023

2.0 SPS07 (April 4, 2023), April 2023

17, July 2015

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT License

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

All OS with a Java VM (>= 1.8)

BSD
Linux
OS X
Solaris
Windows

Appliance or cloud-service

AIX
HP-UX
Linux
OS X
Solaris
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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

Server-side scripts

Stored procedures

yes

SQLScript, R

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

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

none

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

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

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