DBMS > Brytlyt vs. DolphinDB vs. Hazelcast vs. Microsoft SQL Server vs. PostGIS

System Properties Comparison Brytlyt vs. DolphinDB vs. Hazelcast vs. Microsoft SQL Server vs. PostGIS

Editorial information provided by DB-Engines

Name

Description

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

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

A widely adopted in-memory data grid

Microsofts flagship relational DBMS

Spatial extension of PostgreSQL

Primary database model

Secondary database models

Relational DBMS

Document store

JSON support with IMDG 3.12

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Website

brytlyt.io

www.dolphindb.com

hazelcast.com

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

postgis.net

Technical documentation

docs.brytlyt.io

docs.dolphindb.cn/en/help200/index.html

hazelcast.org/imdg/docs

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

postgis.net/documentation

Developer

Brytlyt

DolphinDB, Inc

Hazelcast

Microsoft

Initial release

2016

2018

2008

1989

2005

Current release

5.0, August 2023

v2.00.4, January 2022

5.3.6, November 2023

SQL Server 2022, November 2022

3.4.2, February 2024

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is available

Open Source

GPL v2.0

Cloud-based only

Only available as a cloud service

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Implementation language

C, C++ and CUDA

C++

Java

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

All OS with a Java VM

Linux
Windows

Data scheme

yes

schema-free

yes

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

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

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JCache
JPA
Memcached protocol
RESTful HTTP API

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

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

Event Listeners, Executor Services

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

user defined functions

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

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

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Replicated Map

yes, but depending on the SQL-Server Edition

yes

based on PostgreSQL

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 selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

one or two-phase-commit; repeatable reads; read commited

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

Administrators, Users, Groups

Role-based access control

fine grained access rights according to SQL-standard

yes

based on PostgreSQL

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