DBMS > DolphinDB vs. Netezza vs. Oracle Coherence vs. SAP HANA

System Properties Comparison DolphinDB vs. Netezza vs. Oracle Coherence vs. SAP HANA

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Editorial information provided by DB-Engines

Name

Description

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.

Data warehouse and analytics appliance part of IBM PureSystems

Oracles in-memory data grid solution

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

Primary database model

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	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

www.dolphindb.com

www.ibm.com/products/netezza

www.oracle.com/java/coherence

www.sap.com/products/hana.html

Technical documentation

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

docs.oracle.com/en/middleware/standalone/coherence

help.sap.com/hana

Developer

DolphinDB, Inc

IBM

Oracle

SAP

Initial release

2018

2000

2007

2010

Current release

v2.00.4, January 2022

14.1, August 2023

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

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

C++

Java

Server operating systems

Linux
Windows

Linux

included in appliance

All OS with a Java VM

Appliance or cloud-service

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

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

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

JDBC
ODBC
OLE DB

JCache
JPA
RESTful HTTP API

JDBC
ODBC

Supported programming languages

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

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net
C++
Java

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes, with selectable consistency level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

Administrators, Users, Groups

Users with fine-grained authorization concept

authentification to access the cache via certificates or http basic authentication

yes

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