DBMS > Apache Impala vs. JaguarDB vs. Riak TS vs. Tkrzw

System Properties Comparison Apache Impala vs. JaguarDB vs. Riak TS vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Performant, highly scalable DBMS for AI and IoT applications

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Time Series DBMS

Key-value store

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	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

impala.apache.org

www.jaguardb.com

dbmx.net/tkrzw

Technical documentation

impala.apache.org/impala-docs.html

www.jaguardb.com/support.html

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

DataJaguar, Inc.

Open Source, formerly Basho Technologies

Mikio Hirabayashi

Initial release

2013

2015

2020

Current release

4.1.0, June 2022

3.3 July 2023

3.0.0, September 2022

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

GPL V3.0

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++

the server part. Clients available in other languages

Erlang

C++

Server operating systems

Linux

Linux
OS X

Linux
macOS

Data scheme

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.

Secondary indexes

yes

restricted

SQL

Support of SQL

SQL-like DML and DDL statements

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes, limited

APIs and other access methods

JDBC
ODBC

HTTP API
Native Erlang Interface

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

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

using specific database classes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

rights management via user accounts

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More resources

Recent citations in the news

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

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

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

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

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

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New Basho Data Platform Provides Operational Simplicity for Enterprise Big Data Applications
7 June 2015, insideBIGDATA

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26 May 2017, Open Source For You

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