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

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

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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.

Description

Analytic DBMS for Hadoop

A MySQL compatible DBMS with Git-like versioning of data and schema

Serverless Time Series DBMS

Well established RDBMS

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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	0.96
Rank	#193	Overall
	#90	Relational DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Website

impala.apache.org

github.com/dolthub/dolt
www.dolthub.com

hyprcubd.com (offline)

www.actian.com/databases/ingres

Technical documentation

impala.apache.org/impala-docs.html

docs.dolthub.com

docs.actian.com/ingres

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

DoltHub Inc

Hyprcubd, Inc.

Actian Corporation

Initial release

2013

2018

1974

originally developed at University Berkely in early 1970s

Current release

4.1.0, June 2022

11.2, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

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++

Server operating systems

Linux

Linux
macOS
Windows

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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 DML and DDL statements

yes

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

CLI Client
HTTP REST

gRPC (https)

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

Supported programming languages

All languages supporting JDBC/ODBC

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

currently in alpha release

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Ingres Replicator

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

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

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

Only one user is configurable, and must be specified in the config file at startup

token access

fine grained access rights according to SQL-standard

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More resources

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