DBMS > Blueflood vs. GeoSpock vs. Microsoft SQL Server vs. TDSQL for MySQL vs. XTDB

System Properties Comparison Blueflood vs. GeoSpock vs. Microsoft SQL Server vs. TDSQL for MySQL vs. XTDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Scalable TimeSeries DBMS based on Cassandra

Spatial and temporal data processing engine for extreme data scale

Microsofts flagship relational DBMS

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Time Series DBMS

Relational DBMS

Document store

Secondary database models

Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	0.09
Rank	#353	Overall
	#33	Time Series DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	0.82
Rank	#213	Overall
	#97	Relational DBMS

Score	0.09
Rank	#351	Overall
	#47	Document stores

Website

blueflood.io

geospock.com

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

www.tencentcloud.com/products/dcdb

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

github.com/rax-maas/blueflood/wiki

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

www.tencentcloud.com/document/product/1042

www.xtdb.com/docs

Developer

Rackspace

GeoSpock

Microsoft

Tencent

Juxt Ltd.

Initial release

2013

1989

2013

2019

Current release

2.0, September 2019

SQL Server 2022, November 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, Javascript

C++

Clojure

Server operating systems

Linux
OS X

hosted

Linux
Windows

hosted

All OS with a Java 8 (and higher) VM
Linux

Data scheme

predefined scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP REST

JDBC

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

JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

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

C
C#
C++
Java
PHP
Python
Ruby

Clojure
Java

Server-side scripts

Stored procedures

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Automatic sharding

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

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 can be defined per table

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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