DBMS > Apache Impala vs. Hive vs. NSDb vs. Oracle NoSQL

System Properties Comparison Apache Impala vs. Hive vs. NSDb vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Relational DBMS

Time Series DBMS

Document store
Key-value store
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	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

impala.apache.org

hive.apache.org

nsdb.io

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

impala.apache.org/impala-docs.html

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

nsdb.io/Architecture

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

initially developed by Facebook

Oracle

Initial release

2013

2012

2017

2011

Current release

4.1.0, June 2022

3.1.3, April 2022

23.3, December 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Java, Scala

Java

Server operating systems

Linux

All OS with a Java VM

Linux
macOS

Linux
Solaris SPARC/x86

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

optional

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

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Thrift

gRPC
HTTP REST
WebSocket

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C++
Java
PHP
Python

Java
Scala

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

query execution via MapReduce

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

Transaction concepts

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

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users, groups and roles

Access rights for users and roles

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More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

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