DBMS > Brytlyt vs. InfinityDB vs. RocksDB vs. SQream DB vs. VoltDB

System Properties Comparison Brytlyt vs. InfinityDB vs. RocksDB vs. SQream DB vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

A Java embedded Key-Value Store which extends the Java Map interface

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

a GPU-based, columnar RDBMS for big data analytics workloads

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Key-value store

Relational DBMS

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

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

Technical documentation

docs.brytlyt.io

boilerbay.com/infinitydb/manual

github.com/facebook/rocksdb/wiki

docs.sqream.com

docs.voltdb.com

Developer

Brytlyt

Boiler Bay Inc.

Facebook, Inc.

SQream Technologies

VoltDB Inc.

Initial release

2016

2002

2013

2017

2010

Current release

5.0, August 2023

4.0

9.2.1, May 2024

2022.1.6, December 2022

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

BSD

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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.

Implementation language

C, C++ and CUDA

Java

C++

C++, CUDA, Haskell, Java, Scala

Java, C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux

Linux
OS X

for development

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes, ANSI Standard SQL Types

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

manual creation possible, using inversions based on multi-value capability

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

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

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

C++ API
Java API

.Net
JDBC
ODBC

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Java

C
C++
Go
Java
Perl
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

user defined functions in Python

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

horizontal and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

yes

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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

Users and roles with access to stored procedures

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.