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

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

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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

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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

Primary database model

Relational DBMS

Wide column store

Time Series DBMS

Secondary database models

Document store

Vector DBMS

starting with release V5

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

impala.apache.org

brytlyt.io

cassandra.apache.org

Technical documentation

impala.apache.org/impala-docs.html

docs.brytlyt.io

cassandra.apache.org/doc/latest

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

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Brytlyt

Apache Software Foundation

Apache top level project, originally developped by Facebook

Open Source, formerly Basho Technologies

Initial release

2013

2016

2008

2015

Current release

4.1.0, June 2022

5.0, August 2023

4.1.3, July 2023

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache version 2

Open Source

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

C++

C, C++ and CUDA

Java

Erlang

Server operating systems

Linux

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Linux
OS X

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

restricted

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like SELECT, DML and DDL statements (CQL)

yes, limited

APIs and other access methods

JDBC
ODBC

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

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

HTTP API
Native Erlang Interface

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
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

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

no "single point of failure"

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

selectable replication factor

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
Immediate Consistency

can be individually decided for each write operation

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

Atomicity and isolation are supported for single operations

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.

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

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
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Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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