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  1. Stackups
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  4. Databases
  5. HSQLDB vs Microsoft SQL Server

HSQLDB vs Microsoft SQL Server

OverviewDecisionsComparisonAlternatives

Overview

Microsoft SQL Server
Microsoft SQL Server
Stacks21.3K
Followers15.5K
Votes540
HSQLDB
HSQLDB
Stacks449
Followers61
Votes0
GitHub Stars86
Forks37

HSQLDB vs Microsoft SQL Server: What are the differences?

Introduction

HSQLDB (HyperSQL Database) and Microsoft SQL Server are both popular relational database management systems. While they share some similarities, they also have key differences that set them apart.

  1. Operating Systems Compatibility: HSQLDB is a pure Java database system that can run on any operating system with a Java virtual machine. In contrast, Microsoft SQL Server is primarily designed for Windows operating systems, although there are versions that support Linux and macOS as well.

  2. Scalability: Microsoft SQL Server is known for its scalability and ability to handle large amounts of data. It supports distributed database architectures, replication, and high availability features such as clusters and mirroring. On the other hand, HSQLDB is more suitable for small-scale applications where scalability is not a primary concern.

  3. SQL Dialect: HSQLDB and Microsoft SQL Server use different SQL dialects. HSQLDB is based on the SQL-92 standard, with some additional features. Microsoft SQL Server uses Transact-SQL (T-SQL), which includes various extensions and proprietary features. This difference in SQL dialects can affect the compatibility and portability of SQL scripts between the two database systems.

  4. Cost: HSQLDB is open-source and free to use, making it an attractive option for small projects or individuals with budget constraints. On the other hand, Microsoft SQL Server is a commercial product, with various licensing options based on the edition and usage requirements. The cost of Microsoft SQL Server can be significant, especially for larger-scale applications.

  5. Ecosystem and Support: Microsoft SQL Server has a robust ecosystem and a large community of users, along with comprehensive documentation and official support from Microsoft. This can be a significant advantage when it comes to troubleshooting issues and finding resources. HSQLDB, being an open-source project, also has a community of users but may not have the same level of resources and support as Microsoft SQL Server.

  6. Advanced Features: Microsoft SQL Server offers a wide range of advanced features and capabilities, such as data warehousing, business intelligence, and integration with other Microsoft products like Azure. HSQLDB, being a lightweight database system, does not have the same level of advanced features and may not be suitable for complex enterprise-level requirements.

In summary, HSQLDB and Microsoft SQL Server differ in terms of operating systems compatibility, scalability, SQL dialect, cost, ecosystem/support, and advanced features. These differences should be considered when choosing a database system for a specific application or project.

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Advice on Microsoft SQL Server, HSQLDB

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
HSQLDB
HSQLDB

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

It offers a small, fast multi-threaded and transactional database engine with in-memory and disk-based tables and supports embedded and server modes. It includes a powerful command line SQL tool and simple GUI query tools.

-
Original code, based on in-depth study of database theory and the SQL Standard; Extensive syntax compatibility modes for porting from other database systems; The fastest overall open-source SQL implementation for small and medium sized databases; Three transaction control models, including lock based and MVCC models; Fully multi-threaded; Compact code footprint
Statistics
GitHub Stars
-
GitHub Stars
86
GitHub Forks
-
GitHub Forks
37
Stacks
21.3K
Stacks
449
Followers
15.5K
Followers
61
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
Integrations
No integrations available
Cloud 66
Cloud 66
Leftronic
Leftronic
Spring Boot
Spring Boot
Woopra
Woopra

What are some alternatives to Microsoft SQL Server, HSQLDB?

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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