DBMS > Apache Impala vs. STSdb vs. TempoIQ vs. Transwarp Hippo

System Properties Comparison Apache Impala vs. STSdb vs. TempoIQ vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

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

Description

Analytic DBMS for Hadoop

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

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

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Secondary database models

Document store

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Score	0.00
Rank	#385	Overall
	#16	Vector DBMS

Website

impala.apache.org

github.com/STSSoft/STSdb4

tempoiq.com (offline)

www.transwarp.cn/en/subproduct/hippo

Technical documentation

impala.apache.org/impala-docs.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

STS Soft SC

TempoIQ

Initial release

2013

2011

2012

2023

Current release

4.1.0, June 2022

4.0.8, September 2015

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPLv2, commercial license available

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

Windows

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

yes

Vector, Numeric and 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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

.NET Client API

HTTP API

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C#
Java

C#
Java
JavaScript

Node.js
Python
Ruby

C++
Java
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

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

Transaction concepts

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

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

based on Apache Sentry and Kerberos

simple authentication-based access control

Role based access control and fine grained access rights

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More resources

Recent citations in the news

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29 July 2021, iProgrammer

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28 November 2017, SDTimes.com

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12 March 2017, Uber

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