DBMS > Apache Phoenix vs. DolphinDB vs. SAP HANA

System Properties Comparison Apache Phoenix vs. DolphinDB vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

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.

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

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

phoenix.apache.org

www.dolphindb.com

www.sap.com/products/hana.html

Technical documentation

phoenix.apache.org

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

help.sap.com/hana

Developer

Apache Software Foundation

DolphinDB, Inc

SAP

Initial release

2014

2018

2010

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

v2.00.4, January 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free community version available

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

C++

Server operating systems

Linux
Unix
Windows

Linux
Windows

Appliance or cloud-service

Data scheme

yes

late-bound, schema-on-read capabilities

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

yes

SQL-like query language

yes

APIs and other access methods

JDBC

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

JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

Server-side scripts

Stored procedures

user defined functions

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Administrators, Users, Groups

yes

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