DBMS > Brytlyt vs. CockroachDB vs. GeoMesa vs. IBM Cloudant vs. Microsoft SQL Server

System Properties Comparison Brytlyt vs. CockroachDB vs. GeoMesa vs. IBM Cloudant 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

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

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

Database as a Service offering based on Apache CouchDB

Microsofts flagship relational DBMS

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	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

brytlyt.io

www.cockroachlabs.com

www.geomesa.org

www.ibm.com/products/cloudant

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

Technical documentation

docs.brytlyt.io

www.cockroachlabs.com/docs

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

cloud.ibm.com/docs/Cloudant

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

Developer

Brytlyt

Cockroach Labs

CCRi and others

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

Initial release

2016

2015

2014

2010

1989

Current release

5.0, August 2023

23.1.1, May 2023

4.0.5, February 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0, commercial license available

Open Source

Apache License 2.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C, C++ and CUDA

Scala

Erlang

C++

Server operating systems

Linux
OS X
Windows

Linux
macOS
Windows

hosted

Linux
Windows

Data scheme

yes

dynamic schema

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

Secondary indexes

yes

SQL

Support of SQL

yes

yes, wire compatible with PostgreSQL

yes

APIs and other access methods

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

JDBC

RESTful HTTP/JSON API

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

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

View functions (Map-Reduce) in JavaScript

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

depending on storage layer

Sharding

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

Multi-source replication using RAFT

depending on storage layer

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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.

depending on storage layer

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control

yes

depending on the DBMS used for storage

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

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