DBMS > Amazon DocumentDB vs. Axibase vs. Blueflood vs. Microsoft SQL Server vs. Trafodion

System Properties Comparison Amazon DocumentDB vs. Axibase vs. Blueflood 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

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Scalable TimeSeries DBMS based on Cassandra

Microsofts flagship relational DBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Document 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	1.91
Rank	#131	Overall
	#24	Document stores

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

aws.amazon.com/documentdb

axibase.com/docs/atsd/finance

blueflood.io

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

trafodion.apache.org

Technical documentation

aws.amazon.com/documentdb/resources

github.com/rax-maas/blueflood/wiki

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

trafodion.apache.org/documentation.html

Developer

Axibase Corporation

Rackspace

Microsoft

Apache Software Foundation, originally developed by HP

Initial release

2019

2013

1989

2014

Current release

15585

SQL Server 2022, November 2022

2.3.0, February 2019

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

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

yes

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Implementation language

Java

C++

C++, Java

Server operating systems

hosted

Linux

Linux
OS X

Linux
Windows

Linux

Data scheme

schema-free

yes

predefined scheme

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

HTTP REST

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

ADO.NET
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Go
Java
PHP
Python
R
Ruby

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

yes

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

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Source-replica replication

selectable replication factor

based on Cassandra

yes, but depending on the SQL-Server Edition

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

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

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

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