Overview

Microsoft SQL Server

Stacks21.3K

Followers15.5K

Votes540

MapD

Stacks32

Followers24

Votes4

MapD vs Microsoft SQL Server: What are the differences?

# Key Differences between MapD and Microsoft SQL Server

MapD is an open-source SQL accelerator database, while Microsoft SQL Server is a relational database management system developed by Microsoft. One significant difference between the two is that MapD is designed for interactive analytics on large datasets, providing fast query performance for visualization and analysis tasks. In contrast, Microsoft SQL Server is a more general-purpose database system with a broader range of capabilities, including traditional transactional processing, business intelligence, and reporting functionalities.

1. **Parallel Processing**: MapD utilizes GPU-based parallel processing for query execution, enabling high-speed data processing and computation. On the other hand, Microsoft SQL Server primarily relies on traditional CPU-based processing, which may limit performance when dealing with massive datasets and complex queries.
2. **Visualization Capabilities**: MapD is optimized for interactive data visualization, offering built-in support for rendering high-resolution charts and graphs directly from query results. In comparison, Microsoft SQL Server may require integration with additional BI tools or applications for advanced visualization features.
3. **Deployment Flexibility**: MapD can be easily deployed on-premises, in the cloud, or in a hybrid environment, providing flexibility in setting up the database infrastructure. Microsoft SQL Server, while also supporting various deployment options, may require more configuration and management effort for complex deployment scenarios.
4. **Data Compression Techniques**: MapD employs specialized data compression techniques, such as GPU-friendly columnar storage formats, to optimize memory utilization and query performance. In contrast, Microsoft SQL Server uses conventional compression methods, which may not be as efficient in reducing storage requirements and improving query speeds.
5. **Geospatial Analysis**: MapD has native support for geospatial data types and functions, making it well-suited for geospatial analysis and location-based queries. While Microsoft SQL Server also offers geospatial capabilities, the level of integration and performance in handling spatial data may differ between the two systems.

In Summary, MapD and Microsoft SQL Server differ in their focus on analytics performance, deployment options, visualization support, data processing techniques, and geospatial analysis capabilities.

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Advice on Microsoft SQL Server, MapD

Erin

IT Specialist

Mar 10, 2020

Needs adviceon

Microsoft SQL Server

MySQL

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I am a Microsoft SQL Server programmer who is a bit out of practice. I have been asked to assist on a new project. The overall purpose is to organize a large number of recordings so that they can be searched. I have an enormous music library but my songs are several hours long. I need to include things like time, date and location of the recording. I don't have a problem with the general database design. I have two primary questions:

I need to use either @{MySQL}|tool:1025| or @{PostgreSQL}|tool:1028| on a @{Linux}|tool:10483| based OS. Which would be better for this application?
I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.

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Detailed Comparison

Microsoft SQL Server	MapD
Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.	Interactively query and visualize massive datasets with the parallel power of GPUs.
-	SQL; GPU-powered; column store; fast; scalable; interactive visualization; machine learning
Statistics
Stacks 21.3K	Stacks 32
Followers 15.5K	Followers 24
Votes 540	Votes 4
Pros & Cons
Pros 139 Reliable and easy to use 101 High performance 95 Great with .net 65 Works well with .net 56 Easy to maintain Cons 4 Expensive Licensing 2 Microsoft 1 The maximum number of connections is only 14000 connect 1 Replication can loose the data 1 Allwayon can loose data in asycronious mode	Pros 3 Super fast, and the approach taken 1 Hehe
Integrations
No integrations available	Hadoop Amazon S3 Apache Spark Amazon Redshift MySQL Kafka PostgreSQL IBM DB2 Oracle

What are some alternatives to Microsoft SQL Server, MapD?

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.