DBMS > Apache Impala vs. Hyprcubd vs. Ingres vs. IRONdb

System Properties Comparison Apache Impala vs. Hyprcubd vs. Ingres vs. IRONdb

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Editorial information provided by DB-Engines

Name

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

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

Serverless Time Series DBMS

Well established RDBMS

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Primary database model

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Website

impala.apache.org

hyprcubd.com (offline)

www.actian.com/databases/ingres

www.circonus.com/solutions/time-series-database/

Technical documentation

impala.apache.org/impala-docs.html

docs.actian.com/ingres

docs.circonus.com/irondb/category/getting-started

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Hyprcubd, Inc.

Actian Corporation

Circonus LLC.

Initial release

2013

1974

originally developed at University Berkely in early 1970s

2017

Current release

4.1.0, June 2022

11.2, May 2022

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache Version 2

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

C++

C and C++

Server operating systems

Linux

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

text, numeric, histograms

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 DML and DDL statements

SQL-like query language

yes

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

JDBC
ODBC

gRPC (https)

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Automatic, metric affinity per node

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Ingres Replicator

configurable replication factor, datacenter aware

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

yes

Transaction concepts

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

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.

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

token access

fine grained access rights according to SQL-standard

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More resources

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