DBMS > Brytlyt vs. Cassandra vs. Ehcache vs. LevelDB vs. Riak TS

System Properties Comparison Brytlyt vs. Cassandra vs. Ehcache vs. LevelDB vs. Riak TS

Editorial information provided by DB-Engines

Name

Description

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

A widely adopted Java cache with tiered storage options

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

Primary database model

Secondary database models

Vector DBMS

starting with release V5

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

brytlyt.io

cassandra.apache.org

www.ehcache.org

github.com/google/leveldb

Technical documentation

docs.brytlyt.io

cassandra.apache.org/doc/latest

www.ehcache.org/documentation

github.com/google/leveldb/blob/main/doc/index.md

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

Developer

Brytlyt

Apache Software Foundation

Apache top level project, originally developped by Facebook

Terracotta Inc, owned by Software AG

Google

Open Source, formerly Basho Technologies

Initial release

2016

2008

2009

2011

2015

Current release

5.0, August 2023

4.1.3, July 2023

3.10.0, March 2022

1.23, February 2021

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache Version 2; commercial licenses available

Open Source

BSD

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++ and CUDA

Java

C++

Erlang

Server operating systems

Linux
OS X
Windows

BSD
Linux
OS X
Windows

All OS with a Java VM

Illumos
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

yes

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

yes, limited

APIs and other access methods

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

Proprietary protocol

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

JCache

HTTP API
Native Erlang Interface

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Java

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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

user defined functions

in PL/pgSQL

Erlang

Triggers

yes

Cache Event Listeners

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

by using Terracotta Server

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

yes

by using Terracotta Server

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Tunable Consistency (Strong, Eventual, Weak)

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

Atomicity and isolation are supported for single operations

yes

supports JTA and can work as an XA resource

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

with automatic compression on writes

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

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

More information provided by the system vendor

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