DBMS > Apache Impala vs. Citus vs. InfinityDB vs. NSDb

System Properties Comparison Apache Impala vs. Citus vs. InfinityDB vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A Java embedded Key-Value Store which extends the Java Map interface

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

Primary database model

Relational DBMS

Key-value store

Time Series 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	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

docs.citusdata.com

boilerbay.com/infinitydb/manual

nsdb.io/Architecture

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Boiler Bay Inc.

Initial release

2013

2010

2002

2017

Current release

4.1.0, June 2022

8.1, December 2018

4.0

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

AGPL, commercial license also available

commercial

Open Source

Apache Version 2.0

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

Server operating systems

Linux

All OS with a Java VM

Linux
macOS

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes: int, bigint, decimal, 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.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

all fields are automatically indexed

SQL

Support of SQL

SQL-like DML and DDL statements

yes

standard, with numerous extensions

SQL-like query language

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

gRPC
HTTP REST
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java

Java
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

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

Source-replica replication

other methods possible by using 3rd party extensions

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

READ-COMMITTED or SERIALIZED

Eventual Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

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24 January 2019, blogs.microsoft.com

Microsoft Benchmarks Distributed PostgreSQL DBs
10 July 2023, Datanami

Distributed PostgreSQL Benchmarks: Azure Cosmos DB, CockroachDB, and YugabyteDB
8 July 2023, InfoQ.com

provided by Google News

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