DBMS > Brytlyt vs. HBase vs. HEAVY.AI vs. RocksDB

System Properties Comparison Brytlyt vs. HBase vs. HEAVY.AI vs. RocksDB

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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 Apache Hadoop and on concepts of BigTable

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

brytlyt.io

hbase.apache.org

github.com/heavyai/heavydb
www.heavy.ai

rocksdb.org

Technical documentation

docs.brytlyt.io

hbase.apache.org/book.html

docs.heavy.ai

github.com/facebook/rocksdb/wiki

Developer

Brytlyt

Apache Software Foundation

Apache top-level project, originally developed by Powerset

HEAVY.AI, Inc.

Facebook, Inc.

Initial release

2016

2008

2016

2013

Current release

5.0, August 2023

2.3.4, January 2021

5.10, January 2022

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache Version 2; enterprise edition available

Open Source

BSD

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++ and CUDA

Java

C++ and CUDA

C++

Server operating systems

Linux
OS X
Windows

Linux
Unix
Windows

using Cygwin

Linux

Data scheme

yes

schema-free, schema definition possible

yes

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

SQL

Support of SQL

yes

APIs and other access methods

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

Java API
RESTful HTTP API
Thrift

JDBC
ODBC
Thrift
Vega

C++ API
Java API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C
C#
C++
Groovy
Java
PHP
Python
Scala

All languages supporting JDBC/ODBC/Thrift
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

Coprocessors in Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

yes

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

fine grained access rights according to SQL-standard

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