DBMS > Brytlyt vs. Microsoft SQL Server vs. RavenDB vs. Realm vs. TerarkDB

System Properties Comparison Brytlyt vs. Microsoft SQL Server vs. RavenDB vs. Realm vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

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

Microsofts flagship relational DBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Relational DBMS

Document store

Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

brytlyt.io

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

ravendb.net

realm.io

github.com/bytedance/terarkdb

Technical documentation

docs.brytlyt.io

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

ravendb.net/docs

realm.io/docs

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Brytlyt

Microsoft

Hibernating Rhinos

Realm, acquired by MongoDB in May 2019

ByteDance, originally Terark

Initial release

2016

1989

2010

2014

2016

Current release

5.0, August 2023

SQL Server 2022, November 2022

5.4, July 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

AGPL version 3, commercial license available

Open Source

commercial

restricted open source version available

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++

Server operating systems

Linux
OS X
Windows

Linux
Windows

Linux
macOS
Raspberry Pi
Windows

Android
Backend: server-less
iOS
Windows

Data scheme

yes

schema-free

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

SQL-like query language (RQL)

APIs and other access methods

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

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

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

C++ API
Java API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

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

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Java

with Android only
Objective-C
React Native
Swift

C++
Java

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

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

yes

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, but depending on the SQL-Server Edition

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

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

In-Memory realm

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

yes

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