DBMS > Axibase vs. DolphinDB vs. Hyprcubd vs. Ingres vs. Netezza

System Properties Comparison Axibase vs. DolphinDB vs. Hyprcubd vs. Ingres vs. Netezza

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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.

Serverless Time Series DBMS

Well established RDBMS

Data warehouse and analytics appliance part of IBM PureSystems

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	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Website

axibase.com/docs/atsd/finance

www.dolphindb.com

hyprcubd.com (offline)

www.actian.com/databases/ingres

www.ibm.com/products/netezza

Technical documentation

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

docs.actian.com/ingres

Developer

Axibase Corporation

DolphinDB, Inc

Hyprcubd, Inc.

Actian Corporation

IBM

Initial release

2013

2018

1974

originally developed at University Berkely in early 1970s

2000

Current release

15585

v2.00.4, January 2022

11.2, May 2022

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

free community version available

commercial

Cloud-based only

Only available as a cloud service

yes

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

Linux
Windows

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux

included in appliance

Data scheme

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

time, int, uint, float, string

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

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

gRPC (https)

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JDBC
ODBC
OLE DB

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Ingres Replicator

Source-replica replication

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

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

MVCC

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

Administrators, Users, Groups

token access

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

The Ultimate ATV Test: Suzuki's King Quad 750 AXI Rugged Package vs. Alaska's Hunting Season
14 October 2020, Outdoor Life

provided by Google News

Actian Launches Ingres 12.0 Database
4 June 2024, PR Newswire

Postgres pioneer Michael Stonebraker promises to upend the database once more
26 December 2023, The Register

Actian Launches Ingres as a Fully-Managed Cloud Service
24 September 2021, Integration Developers

Dr. Michael Stonebraker: A Short History of Database Systems
1 February 2019, The New Stack

New startup from Postgres creator puts the database at heart of software stack
12 March 2024, TechCrunch

provided by Google News

Roundup: Telehouse, Cloudera, Netezza, EMC
31 May 2024, Data Center Knowledge

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, IBM

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

provided by Google News

Share this page