DBMS > Brytlyt vs. Cassandra vs. Hazelcast vs. Realm vs. Tibero

System Properties Comparison Brytlyt vs. Cassandra vs. Hazelcast vs. Realm vs. Tibero

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 in-memory data grid

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Secondary database models

Vector DBMS

starting with release V5

Document store

JSON support with IMDG 3.12

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	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

us.tmaxsoft.com/products/tibero

Technical documentation

docs.brytlyt.io

cassandra.apache.org/doc/latest

hazelcast.org/imdg/docs

realm.io/docs

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Brytlyt

Apache Software Foundation

Apache top level project, originally developped by Facebook

Hazelcast

Realm, acquired by MongoDB in May 2019

TmaxSoft

Initial release

2016

2008

2014

2003

Current release

5.0, August 2023

4.1.3, July 2023

5.3.6, November 2023

6, April 2015

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache Version 2; commercial licenses available

Open Source

commercial

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 and Assembler

Server operating systems

Linux
OS X
Windows

BSD
Linux
OS X
Windows

All OS with a Java VM

Android
Backend: server-less
iOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

yes

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.

yes

the object must implement a serialization strategy

yes

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

yes

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

SQL-like query language

yes

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
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

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

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

.Net
Java

with Android only
Objective-C
React Native
Swift

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

Event Listeners, Executor Services

runs within the applications so server-side scripts are unnecessary

Persistent Stored Procedure (PSM)

Triggers

yes

Events

yes

Change Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

none

horizontal partitioning

by range, hash, list or composite

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

Replicated Map

none

Multi-source replication
Source-replica replication

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

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

one or two-phase-commit; repeatable reads; read commited

ACID

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

In-Memory realm

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

Role-based access control

yes

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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

No single point of failure ensures 100% availability . Operational simplicity for...
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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...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

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