DBMS > Apache IoTDB vs. DolphinDB vs. PostgreSQL vs. SAP Adaptive Server vs. SAP Advantage Database Server

System Properties Comparison Apache IoTDB vs. DolphinDB vs. PostgreSQL vs. SAP Adaptive Server 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

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

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

Primary database model

Time Series DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Website

iotdb.apache.org

www.dolphindb.com

www.postgresql.org

www.sap.com/products/technology-platform/sybase-ase.html

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

Technical documentation

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

docs.dolphindb.cn/en/help200/index.html

www.postgresql.org/docs

help.sap.com/docs/SAP_ASE

Developer

Apache Software Foundation

DolphinDB, Inc

PostgreSQL Global Development Group

www.postgresql.org/developer

SAP, Sybase

Sybase, SAP

Initial release

2018

1989

1989: Postgres, 1996: PostgreSQL

1987

1993

Current release

1.1.0, April 2023

v2.00.4, January 2022

16.3, May 2024

16.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community version available

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

C and C++

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Linux
Windows

Data scheme

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

standard with numerous extensions

yes

APIs and other access methods

JDBC
Native API

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Cobol
Java
Java
Perl
PHP
Python

Delphi
Perl
PHP

Server-side scripts

Stored procedures

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Java and Transact-SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

partitioning by range, list and (since PostgreSQL 11) by hash

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

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication
Source-replica replication

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

yes

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

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

caching of (temporary) tables can be configured

User concepts

Access control

yes

Administrators, Users, Groups

fine grained access rights according to SQL-standard

More information provided by the system vendor

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