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

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

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

High performance Time Series DBMS

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

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

Primary database model

Relational DBMS

Key-value store

Time Series DBMS
Vector DBMS

Key-value store

Relational DBMS

Secondary database models

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	7.71
Rank	#49	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

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

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

Technical documentation

docs.brytlyt.io

boilerbay.com/infinitydb/manual

code.kx.com

github.com/facebook/rocksdb/wiki

docs.sqream.com

Developer

Brytlyt

Boiler Bay Inc.

Kx Systems, a division of First Derivatives plc

Facebook, Inc.

SQream Technologies

Initial release

2016

2002

2000

kdb was released 2000, kdb+ in 2003

2013

2017

Current release

5.0, August 2023

4.0

3.6, May 2018

9.2.1, May 2024

2022.1.6, December 2022

License

Commercial or Open Source

commercial

free 32-bit version

Open Source

BSD

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.

Implementation language

C, C++ and CUDA

Java

C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

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

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

yes

yes, ANSI Standard SQL Types

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

Secondary indexes

yes

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

yes

table attribute 'grouped'

SQL

Support of SQL

yes

SQL-like query language (q)

yes

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)

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

C++ API
Java API

.Net
JDBC
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Java

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

C
C++
Go
Java
Perl
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

user defined functions

user defined functions in Python

Triggers

yes

with views

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

similar paradigm used for internal processing

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

yes

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

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

rights management via user accounts

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
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