DBMS > Apache IoTDB vs. BigchainDB vs. Heroic vs. JaguarDB vs. SAP Advantage Database Server

System Properties Comparison Apache IoTDB vs. BigchainDB vs. Heroic vs. JaguarDB vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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

Performant, highly scalable DBMS for AI and IoT applications

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Time Series DBMS

Document store

Time Series DBMS

Key-value store
Vector DBMS

Relational DBMS

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

Score	1.19
Rank	#176	Overall
	#15	Time Series DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	0.09
Rank	#356	Overall
	#53	Key-value stores
	#13	Vector DBMS

Website

iotdb.apache.org

www.bigchaindb.com

github.com/spotify/heroic

www.jaguardb.com

www.sap.com/products/advantage-database-server.html

Technical documentation

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

bigchaindb.readthedocs.io/en/latest

spotify.github.io/heroic

www.jaguardb.com/support.html

Developer

Apache Software Foundation

Spotify

DataJaguar, Inc.

Sybase, SAP

Initial release

2018

2016

2014

2015

1993

Current release

1.1.0, April 2023

3.3 July 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL v3

Open Source

Apache 2.0

Open Source

GPL V3.0

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.

Implementation language

Java

Python

Java

C++

the server part. Clients available in other languages

Server operating systems

All OS with a Java VM (>= 1.8)

Linux

Linux
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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

JDBC
Native API

CLI Client
RESTful HTTP API

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

JDBC
ODBC

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

Go
Haskell
Java
JavaScript
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Delphi
Perl
PHP

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

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

selectable replication factor

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

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

Eventual Consistency
Immediate Consistency

Eventual 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

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

caching of (temporary) tables can be configured

User concepts

Access control

yes

rights management via user accounts

fine grained access rights according to SQL-standard

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