DBMS > Apache Druid vs. Brytlyt vs. GeoMesa vs. Microsoft SQL Server vs. Tibero

System Properties Comparison Apache Druid vs. Brytlyt vs. GeoMesa vs. Microsoft SQL Server vs. Tibero

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

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

Relational DBMS
Time Series DBMS

Relational DBMS

Spatial 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	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

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

druid.apache.org

brytlyt.io

www.geomesa.org

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

us.tmaxsoft.com/products/tibero

Technical documentation

druid.apache.org/docs/latest/design

docs.brytlyt.io

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

Apache Software Foundation and contributors

Brytlyt

CCRi and others

Microsoft

TmaxSoft

Initial release

2012

2016

2014

1989

2003

Current release

29.0.1, April 2024

5.0, August 2023

5.0.0, May 2024

SQL Server 2022, November 2022

6, April 2015

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache License 2.0

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C, C++ and CUDA

Scala

C++

C and Assembler

Server operating systems

Linux
OS X
Unix

Linux
OS X
Windows

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-less columns are supported

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

SQL for querying

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

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

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

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

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C++
Delphi
Java
Perl
Python
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

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

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

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

yes, via HDFS, S3 or other storage engines

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

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

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.

depending on storage layer

yes

planned for next version

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

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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