DBMS > Brytlyt vs. Datomic vs. Graph Engine vs. Graphite vs. Microsoft SQL Server

System Properties Comparison Brytlyt vs. Datomic vs. Graph Engine vs. Graphite vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Time Series DBMS

Relational DBMS

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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

brytlyt.io

www.datomic.com

www.graphengine.io

github.com/graphite-project/graphite-web

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

Technical documentation

docs.brytlyt.io

docs.datomic.com

www.graphengine.io/docs/manual

graphite.readthedocs.io

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

Developer

Brytlyt

Cognitect

Microsoft

Chris Davis

Microsoft

Initial release

2016

2012

2010

2006

1989

Current release

5.0, August 2023

1.0.6735, June 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

limited edition free

Open Source

MIT License

Open Source

Apache 2.0

commercial

restricted free version is available

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, Clojure

.NET and C

Python

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

.NET

Linux
Unix

Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

RESTful HTTP API

HTTP API
Sockets

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

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Clojure
Java

C#
C++
F#
Visual Basic

JavaScript (Node.js)
Python

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

Transaction Functions

yes

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

Triggers

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

horizontal partitioning

none

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

But extensive use of caching in the application peers

none

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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