DBMS > Apache IoTDB vs. jBASE vs. MySQL vs. RocksDB vs. SAP Advantage Database Server

System Properties Comparison Apache IoTDB vs. jBASE vs. MySQL vs. RocksDB 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

A robust multi-value DBMS comprising development tools and middleware

Widely used open source RDBMS

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Primary database model

Time Series DBMS

Multivalue DBMS

Relational DBMS

Key/Value like access via memcached API

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

iotdb.apache.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.mysql.com

rocksdb.org

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

Technical documentation

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

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

dev.mysql.com/doc

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Rocket Software (formerly Zumasys)

Oracle

since 2010, originally MySQL AB, then Sun

Facebook, Inc.

Sybase, SAP

Initial release

2018

1991

1995

2013

1993

Current release

1.1.0, April 2023

5.7

8.4.0, April 2024

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C and C++

C++

Server operating systems

All OS with a Java VM (>= 1.8)

AIX
Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Linux
Windows

Data scheme

yes

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

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

Embedded SQL for jBASE in BASIC

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
Native API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
JDBC
ODBC
Proprietary native API

C++ API
Java API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
Basic
Jabbascript
Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C
C++
Go
Java
Perl
Python
Ruby

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

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

Multi-source replication
Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

caching of (temporary) tables can be configured

User concepts

Access control

yes

Access rights can be defined down to the item level

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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