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Apache Doris VS Microsoft SQL

Compare Apache Doris VS Microsoft SQL and see what are their differences

Apache Doris logo Apache Doris

Apache Doris is an open-source real-time data warehouse for big data analytics.

Microsoft SQL logo Microsoft SQL

Microsoft SQL is a best in class relational database management software that facilitates the database server to provide you a primary function to store and retrieve data.
  • Apache Doris Apache Doris
    Apache Doris //
    2024-01-10
  • Microsoft SQL Landing page
    Landing page //
    2023-01-26

Apache Doris features and specs

  • High Performance
    Apache Doris is designed to deliver high query performance, especially for aggregate queries, due to its columnar storage and vectorized execution engine.
  • Real-time Analytics
    Supports real-time data analytics with low latency, thanks to its efficient data ingestion processes and real-time data update capabilities.
  • Unified Analytics
    Provides a unified platform that supports both real-time and batch data processing, offering flexibility for different analytical workloads.
  • Ease of Use
    Features a SQL-like interface, which makes it accessible for users familiar with SQL, reducing the learning curve.
  • Scalability
    Can scale out horizontally, allowing it to handle increasing volumes of data and user queries by adding more nodes to the cluster.

Possible disadvantages of Apache Doris

  • Ecosystem Integration
    While improving, the ecosystem isn't as mature as older database management systems, which might pose integration challenges with certain tools.
  • Community Support
    Being a relatively newer project, it may not have as large a community or as extensive third-party support as more established databases.
  • Complexity in Setup
    Initial setup and configuration can be complex, especially for users not already familiar with similar distributed systems.
  • Limited Use Cases
    Optimized specifically for online analytical processing (OLAP), it may not be suitable for all types of databases or transactional use cases.
  • Features Maturity
    Some features may lack the maturity and robustness found in more mature and widely adopted database systems, requiring careful evaluation based on project needs.

Microsoft SQL features and specs

  • Comprehensive Feature Set
    SQL Server offers a wide range of features including advanced analytics, in-memory capabilities, robust security measures, and integration services.
  • High Performance
    With in-memory OLTP and support for persistent memory technologies, SQL Server provides high transaction and query performance.
  • Scalability
    SQL Server can scale from small installations on single machines to large, data-intensive applications requiring high throughput and storage.
  • Security
    SQL Server offers advanced security features like encryption, dynamic data masking, and advanced threat protection, ensuring data safety and compliance.
  • Integrations
    It easily integrates with other Microsoft products such as Azure, Power BI, and Active Directory, providing a cohesive ecosystem for enterprise solutions.
  • Developer Friendly
    It supports a wide range of development tools and languages including .NET, Python, Java, and more, making it highly versatile for developers.
  • High Availability
    Features like Always On availability groups and failover clustering provide high availability and disaster recovery options for critical applications.

Possible disadvantages of Microsoft SQL

  • Cost
    SQL Server can be expensive, particularly for the Enterprise edition. Licensing costs can add up quickly depending on the features and scale required.
  • Complexity
    Due to its comprehensive feature set, SQL Server can be complex to configure and manage, requiring skilled administrators and developers.
  • Resource Intensive
    SQL Server can be resource-intensive, requiring substantial hardware resources for optimal performance, which can increase overall operational costs.
  • Windows-Centric
    While SQL Server can run on Linux, it is primarily optimized for and tightly integrated with the Windows ecosystem, which may not suit all organizations.
  • Vendor Lock-In
    Being a proprietary solution, it can cause vendor lock-in, making it challenging to switch to alternative database systems without significant migration efforts.

Analysis of Microsoft SQL

Overall verdict

  • Yes, Microsoft SQL Server is generally regarded as a good choice for database management, particularly for organizations that require high performance, reliability, and seamless integration with other Microsoft technologies.

Why this product is good

  • Microsoft SQL Server is considered a robust database management system because of its comprehensive features such as high scalability, strong security, and excellent integration with other Microsoft products. It provides tools for data mining, warehousing, and analytics, making it a popular choice for enterprises. Additionally, it offers high availability and disaster recovery solutions, and its active community provides extensive support and resources.

Recommended for

  • Enterprises
  • Businesses using Microsoft ecosystems
  • Organizations requiring robust data security
  • Users needing scalability for large datasets
  • Projects needing high availability and disaster recovery

Apache Doris videos

No Apache Doris videos yet. You could help us improve this page by suggesting one.

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Microsoft SQL videos

3.1 Microsoft SQL Server Review

More videos:

  • Review - What is Microsoft SQL Server?
  • Review - Querying Microsoft SQL Server (T-SQL) | Udemy Instructor, Phillip Burton [bestseller]

Category Popularity

0-100% (relative to Apache Doris and Microsoft SQL)
Databases
3 3%
97% 97
Data Warehousing
100 100%
0% 0
Relational Databases
2 2%
98% 98
Tool
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Doris and Microsoft SQL

Apache Doris Reviews

Log analysis: Elasticsearch vs Apache Doris
If you are looking for an efficient log analytic solution, Apache Doris is friendly to anyone equipped with SQL knowledge; if you find friction with the ELK stack, try Apache Doris provides better schema-free support, enables faster data writing and queries, and brings much less storage burden.

Microsoft SQL Reviews

MCP Servers for Test Data: What Exists and What Each One Does
A test-data MCP server is one whose tools generate realistic, relationally consistent rows and write them into a database, so an AI coding agent can populate an empty schema by describing what it needs in plain language. It's distinct from the far more common database-access MCP, which only reads or queries data that already exists. Seedfast is an example of the generating...
Source: dev.to

Social recommendations and mentions

Based on our record, Apache Doris seems to be more popular. It has been mentiond 9 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Apache Doris mentions (9)

  • Apache Doris 4.0: One Engine for Analytics, Full-Text Search, and Vector Search
    The latest version of Apache Doris is now available for download. Visit doris.apache.org for detailed release notes and upgrade guides, and join the Doris community to explore, test, and share your feedback. - Source: dev.to / 10 months ago
  • Doris x Gravitino: Unified Metadata Management for Modern Lakehouse Architecture
    This article provides an in-depth introduction to deep integration between Apache Doris and Apache Gravitino, building a modern lakehouse architecture based on Iceberg REST Catalog. Through Gravitino's unified metadata management and dynamic credential vending capabilities, we achieve efficient and secure access to Iceberg data stored on S3. - Source: dev.to / 11 months ago
  • Gravitino 0.5.0: Expanding the horizon to Apache Spark, non-tabular data, and more!
    Tagging onto our Real-Time Analytics support, we are now also supporting Apache Doris in this release. Doris is a high-performance, real-time analytical data warehouse that is known for its speed and ease of use. By adding a Doris catalog, engineers implementing Gravitino will now have more flexibility in their cataloging options for their analytical workloads. (Issue #1339, visit jdbc-doris-catalog for... - Source: dev.to / about 1 year ago
  • Evolution of Data Sharding Towards Automation and Flexibility
    Like in many databases, Apache Doris shards data into partitions, and then a partition is further divided into buckets. Partitions are typically defined by time or other continuous values. This allows query engines to quickly locate the target data during queries by pruning irrelevant data ranges. - Source: dev.to / about 2 years ago
  • Steps to industry-leading query speed: evolution of the Apache Doris execution engine
    What makes a modern database system? The three key modules are query optimizer, execution engine, and storage engine. Among them, the role of execution engine to the DBMS is like the chef to a restaurant. This article focuses on the execution engine of the Apache Doris data warehouse, explaining the secret to its high performance. - Source: dev.to / about 2 years ago
View more

Microsoft SQL mentions (0)

We have not tracked any mentions of Microsoft SQL yet. Tracking of Microsoft SQL recommendations started around Mar 2021.

What are some alternatives?

When comparing Apache Doris and Microsoft SQL, you can also consider the following products

ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.

MySQL - The world's most popular open source database

StarRocks - StarRocks offers the next generation of real-time SQL engines for enterprise-scale analytics. Learn how we make it easy to deliver real-time analytics.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

Apache Hive - Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.

Oracle Database 12c - Simplify database management and automate the information lifecycle with maximum security.