DBMS > Apache Impala vs. NSDb vs. ToroDB vs. Typesense

System Properties Comparison Apache Impala vs. NSDb vs. ToroDB vs. Typesense

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.76
Rank	#219	Overall
	#14	Search engines

Website

impala.apache.org

nsdb.io

github.com/torodb/server

typesense.org

Technical documentation

impala.apache.org/impala-docs.html

nsdb.io/Architecture

typesense.org/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

8Kdata

Initial release

2013

2017

2016

2015

Current release

4.1.0, June 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

AGPL-V3

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java, Scala

Java

C++

Server operating systems

Linux

Linux
macOS

All OS with a Java 7 VM

Linux

Data scheme

yes

schema-free

pre-defined schema optional

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

yes

string, integer, double, boolean, date, object_id

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.

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC
ODBC

gRPC
HTTP REST
WebSocket

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Java
Scala

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

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

Source-replica replication

Multi-source replication using RAFT

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

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

Using Apache Lucene

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

Access rights for users and roles

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More resources

Recent citations in the news

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29 July 2021, iProgrammer

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

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28 November 2017, Datanami

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

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24 June 2022, InfoWorld

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