DBMS > Apache IoTDB vs. DolphinDB vs. SAP Advantage Database Server vs. Splice Machine

System Properties Comparison Apache IoTDB vs. DolphinDB vs. SAP Advantage Database Server vs. Splice Machine

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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.

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

iotdb.apache.org

www.dolphindb.com

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

splicemachine.com

Technical documentation

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

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

splicemachine.com/how-it-works

Developer

Apache Software Foundation

DolphinDB, Inc

Sybase, SAP

Splice Machine

Initial release

2018

1993

2014

Current release

1.1.0, April 2023

v2.00.4, January 2022

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community version available

commercial

Open Source

AGPL 3.0, 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++

Java

Server operating systems

All OS with a Java VM (>= 1.8)

Linux
Windows

Linux
OS X
Solaris
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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

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

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

JDBC
Native Spark Datasource
ODBC

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

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

Delphi
Perl
PHP

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

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

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Yes, via Full Spark Integration

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

yes, multi-version concurrency control (MVCC)

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

yes

User concepts

Access control

yes

Administrators, Users, Groups

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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