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

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

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

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

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Relational DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

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

Score	81.61
Rank	#17	Overall
	#11	Relational 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

www.intersystems.com/products/intersystems-iris

www.leanxcale.com

tempoiq.com (offline)

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

InterSystems

LeanXcale

TempoIQ

Initial release

2012

2018

2015

2012

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

All OS with a Java VM

AIX
Linux
macOS
Windows

Data scheme

yes

depending on used data model

yes

schema-free

Typing

predefined data types such as float or date

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

yes

through Apache Derby

APIs and other access methods

JDBC
ODBC
Thrift

JDBC
ODBC
RESTful HTTP API

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP API

Supported programming languages

C++
Java
PHP
Python

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

C
Java
Scala

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Realtime Alerts

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

yes

simple authentication-based access control

More information provided by the system vendor

Specific characteristics

Full ACID and full SQL operational database with analytical queries over operational...
» more

Competitive advantages

Linear scalability upto 100s of nodes (tested with 100 nodes and TPC-C).
» more

Typical application scenarios

Hybrid Transactional-Analytical Processing (HTAP) requiring an operational database...
» more

Key customers

banking/finance/fintech, telco, insurance, traveltech, M2M/IoT, retail
» more

Market metrics

15 beta testers
» more

Licensing and pricing models

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

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.