DBMS > Brytlyt vs. GeoMesa vs. Ignite vs. Microsoft SQL Server vs. Trafodion

System Properties Comparison Brytlyt vs. GeoMesa vs. Ignite vs. Microsoft SQL Server vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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.

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Microsofts flagship relational DBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Spatial DBMS

Key-value store
Relational 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	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

brytlyt.io

www.geomesa.org

ignite.apache.org

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

trafodion.apache.org

Technical documentation

docs.brytlyt.io

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

apacheignite.readme.io/docs

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

trafodion.apache.org/documentation.html

Developer

Brytlyt

CCRi and others

Apache Software Foundation

Microsoft

Apache Software Foundation, originally developed by HP

Initial release

2016

2014

2015

1989

2014

Current release

5.0, August 2023

4.0.5, February 2024

Apache Ignite 2.6

SQL Server 2022, November 2022

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

C, C++ and CUDA

Scala

C++, Java, .Net

C++

C++, Java

Server operating systems

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Linux
Windows

Linux

Data scheme

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

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

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

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C#
C++
Java
PHP
Python
Ruby
Scala

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes (compute grid and cache interceptors can be used instead)

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

Java Stored Procedures

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

depending on storage layer

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

depending on storage layer

yes (replicated cache)

yes, but depending on the SQL-Server Edition

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

yes

via user defined functions and HBase

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

User concepts

Access control

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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