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  1. Stackups
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  4. Databases
  5. H2 Database vs Microsoft SQL Server

H2 Database vs Microsoft SQL Server

OverviewDecisionsComparisonAlternatives

Overview

Microsoft SQL Server
Microsoft SQL Server
Stacks21.3K
Followers15.5K
Votes540
H2 Database
H2 Database
Stacks1.3K
Followers121
Votes0

H2 Database vs Microsoft SQL Server: What are the differences?

Key Differences between H2 Database and Microsoft SQL Server

H2 Database and Microsoft SQL Server are both widely used relational database management systems, but they differ in several key aspects.

  1. Cost: One of the major differences between H2 Database and Microsoft SQL Server is the cost. H2 Database is an open-source database that is available for free, making it a cost-effective option for small projects or individuals. On the other hand, Microsoft SQL Server is a commercial product and requires licensing, making it more suitable for enterprise-level applications or organizations willing to invest in a robust database system.

  2. Platform Compatibility: H2 Database is written in Java and can be used on any platform that supports Java, including Windows, Linux, and macOS. It offers excellent cross-platform compatibility, allowing developers to deploy their applications on different operating systems seamlessly. In contrast, Microsoft SQL Server is primarily designed for the Windows operating system and provides limited support for other platforms, making it less flexible for cross-platform development needs.

  3. Scalability and Performance: Microsoft SQL Server is known for its scalability and performance capabilities, making it a preferred choice for large-scale enterprise applications with high traffic and complex data requirements. It offers advanced features such as indexing, partitioning, and query optimization, allowing for efficient data retrieval and processing. While H2 Database also provides decent performance, it may not scale as well as Microsoft SQL Server in demanding enterprise environments.

  4. Feature Set: Microsoft SQL Server offers a comprehensive range of features, including advanced analytical capabilities, support for business intelligence, and integration with other Microsoft technologies such as .NET framework. It provides enterprise-level features like data replication, server clustering, and high availability options for building robust and reliable systems. On the other hand, H2 Database provides a lightweight and simple feature set, suitable for smaller projects that do not require complex functionality or extensive integrations.

  5. Community and Support: H2 Database has an active community of open-source developers, providing support, documentation, and regular updates. It has a vibrant ecosystem that fosters collaboration and community-driven enhancements. In contrast, Microsoft SQL Server has a larger user base and professional support from Microsoft. It offers comprehensive documentation, official forums, and dedicated customer support services, ensuring reliable assistance for enterprise-level deployments.

  6. Ecosystem Integration: Microsoft SQL Server seamlessly integrates with other Microsoft technologies, such as Azure cloud services, Visual Studio IDE, and .NET framework. This integration facilitates smooth development and deployment processes, offering a unified environment for end-to-end application development. In comparison, H2 Database may require additional configuration or development efforts to integrate with broader technology ecosystems.

In Summary, H2 Database and Microsoft SQL Server differ in terms of cost, platform compatibility, scalability and performance, feature set, community and support, and ecosystem integration. Each has its strengths and suitability depending on the specific requirements of the application or project.

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Advice on Microsoft SQL Server, H2 Database

Erin
Erin

IT Specialist

Mar 10, 2020

Needs adviceonMicrosoft SQL ServerMicrosoft SQL ServerMySQLMySQLPostgreSQLPostgreSQL

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:

  1. 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?
  2. I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.
668k views668k
Comments

Detailed Comparison

Microsoft SQL Server
Microsoft SQL Server
H2 Database
H2 Database

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

It is a relational database management system written in Java. It can be embedded in Java applications or run in client-server mode.

Statistics
Stacks
21.3K
Stacks
1.3K
Followers
15.5K
Followers
121
Votes
540
Votes
0
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
    Replication can loose the data
  • 1
    Allwayon can loose data in asycronious mode
  • 1
    The maximum number of connections is only 14000 connect
No community feedback yet

What are some alternatives to Microsoft SQL Server, H2 Database?

MongoDB

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

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

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

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

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

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

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

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

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

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.

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