DBMS > Apache Impala vs. Brytlyt vs. Riak TS vs. XTDB

System Properties Comparison Apache Impala vs. Brytlyt vs. Riak TS vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Time Series DBMS

Document 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	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

impala.apache.org

brytlyt.io

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

impala.apache.org/impala-docs.html

docs.brytlyt.io

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

www.xtdb.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Brytlyt

Open Source, formerly Basho Technologies

Juxt Ltd.

Initial release

2013

2016

2015

2019

Current release

4.1.0, June 2022

5.0, August 2023

3.0.0, September 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C, C++ and CUDA

Erlang

Clojure

Server operating systems

Linux

Linux
OS X
Windows

Linux
OS X

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

restricted

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

yes, limited

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

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

HTTP API
Native Erlang Interface

HTTP REST
JDBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

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

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

in PL/pgSQL

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

Source-replica replication

selectable replication factor

yes, each node contains all data

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

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

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

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

Opensignal Announces Acquisition of Brytlyt GPU-based Data Analytics & Visualization Technology
5 June 2024, PR Web

Brytlyt releases version 5.0, introducing a more intuitive, intelligent and flexible analytics platform
1 August 2023, PR Newswire

London data analytics startup Brytlyt raises €4.43M from Amsterdam-based Finch Capital, others
22 December 2021, Silicon Canals

Brytlyt Secures $4M in Series A Funding
20 May 2020, Datanami

London’s Brytlyt raises €4.4 million for its data analytics and visualisation technology
22 December 2021, EU-Startups

provided by Google News

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

provided by Google News

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