DBMS > Brytlyt vs. Derby vs. IBM Db2 Event Store vs. RocksDB

System Properties Comparison Brytlyt vs. Derby vs. IBM Db2 Event Store 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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Distributed Event Store optimized for Internet of Things use cases

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

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Key-value store

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

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

Website

brytlyt.io

db.apache.org/derby

www.ibm.com/products/db2-event-store

rocksdb.org

Technical documentation

docs.brytlyt.io

db.apache.org/derby/manuals/index.html

www.ibm.com/docs/en/db2-event-store

github.com/facebook/rocksdb/wiki

Developer

Brytlyt

Apache Software Foundation

IBM

Facebook, Inc.

Initial release

2016

1997

2017

2013

Current release

5.0, August 2023

10.17.1.0, November 2023

2.0

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

free developer edition available

Open Source

BSD

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 and C++

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux

Linux, macOS, Windows for the developer addition

Linux

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

APIs and other access methods

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

JDBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Java

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Active-active shard replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

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