DBMS > Hive vs. Hyprcubd vs. InterSystems IRIS vs. LeanXcale

System Properties Comparison Hive vs. Hyprcubd vs. InterSystems IRIS vs. LeanXcale

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Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Relational DBMS

Time Series DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Key-value store
Relational DBMS

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

Score	81.61
Rank	#17	Overall
	#11	Relational DBMS

Score	0.00
Rank	#354	Overall
	#33	Time Series DBMS

Score	2.25
Rank	#119	Overall
	#22	Document stores
	#23	Key-value stores
	#2	Object oriented DBMS
	#59	Relational DBMS

Score	0.18
Rank	#292	Overall
	#42	Key-value stores
	#136	Relational DBMS

Website

hive.apache.org

hyprcubd.com

www.intersystems.com/products/intersystems-iris

www.leanxcale.com

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

Developer

Apache Software Foundation

initially developed by Facebook

Hyprcubd, Inc.

InterSystems

LeanXcale

Initial release

2012

2018

2015

Current release

3.1.2, August 2019

2021.1, June 2021

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

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Implementation language

Java

Server operating systems

All OS with a Java VM

hosted

AIX
Linux
macOS
Windows

Data scheme

yes

depending on used data model

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

yes

through Apache Derby

APIs and other access methods

JDBC
ODBC
Thrift

gRPC (https)

JDBC
ODBC
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

C++
Java
PHP
Python

.Net
C++
Java
JavaScript (Node.js)
Python

C
Java
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

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

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

Access rights for users, groups and roles

token access

yes

More information provided by the system vendor

Specific characteristics

Full ACID and full SQL operational database with analytical queries over operational...
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Competitive advantages

Linear scalability upto 100s of nodes (tested with 100 nodes and TPC-C).
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Typical application scenarios

Hybrid Transactional-Analytical Processing (HTAP) requiring an operational database...
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Key customers

banking/finance/fintech, telco, insurance, traveltech, M2M/IoT, retail
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Market metrics

15 beta testers
» more

Licensing and pricing models

annual fee covering license and support based on number of physical cores
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