DBMS > Brytlyt vs. Dragonfly vs. GeoMesa vs. Microsoft SQL Server vs. Tibero

System Properties Comparison Brytlyt vs. Dragonfly vs. GeoMesa vs. Microsoft SQL Server vs. Tibero

Editorial information provided by DB-Engines

Name

Description

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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Microsofts flagship relational DBMS

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Website

brytlyt.io

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.geomesa.org

www.microsoft.com/en-us/sql-server

us.tmaxsoft.com/products/tibero

Technical documentation

docs.brytlyt.io

www.dragonflydb.io/docs

www.geomesa.org/documentation/stable/user/index.html

learn.microsoft.com/en-US/sql/sql-server

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

Developer

Brytlyt

DragonflyDB team and community contributors

CCRi and others

Microsoft

TmaxSoft

Initial release

2016

2023

2014

1989

2003

Current release

5.0, August 2023

1.0, March 2023

5.0.0, May 2024

SQL Server 2022, November 2022

6, April 2015

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

Open Source

Apache License 2.0

commercial

restricted free version is available

commercial

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

C++

Scala

C++

C and Assembler

Server operating systems

Linux
OS X
Windows

Linux

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

scheme-free

yes

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

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

APIs and other access methods

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

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

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

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

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

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

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

Lua

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Persistent Stored Procedure (PSM)

Triggers

yes

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

tables can be distributed across several files (horizontal partitioning); sharding through federation

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

depending on storage layer

yes, but depending on the SQL-Server Edition

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

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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

depending on storage layer

yes

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard

Password-based authentication

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

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

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