DBMS > BigObject vs. Infobright vs. Ingres vs. NSDb

System Properties Comparison BigObject vs. Infobright vs. Ingres vs. NSDb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Well established RDBMS

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Time Series DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

bigobject.io

ignitetech.com/softwarelibrary/infobrightdb

www.actian.com/databases/ingres

nsdb.io

Technical documentation

docs.bigobject.io

docs.actian.com/ingres

nsdb.io/Architecture

Developer

BigObject, Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

Actian Corporation

Initial release

2015

2005

1974

originally developed at University Berkely in early 1970s

2017

Current release

11.2, May 2022

License

Commercial or Open Source

commercial

free community edition available

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

Open Source

Apache Version 2.0

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, Scala

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Windows

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

Knowledge Grid Technology used instead

yes

all fields are automatically indexed

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

gRPC
HTTP REST
WebSocket

Supported programming languages

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
Scala

Server-side scripts

Stored procedures

Lua

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Ingres Replicator

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

MVCC

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

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

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

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

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

What is Ingres? - Definition from Techopedia
15 September 2011, Techopedia

provided by Google News

Share this page