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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. DuckDB vs H2 Database

DuckDB vs H2 Database

OverviewComparisonAlternatives

Overview

H2 Database
H2 Database
Stacks1.3K
Followers121
Votes0
DuckDB
DuckDB
Stacks49
Followers60
Votes0

DuckDB vs H2 Database: What are the differences?

Key Differences between DuckDB and H2 Database

DuckDB and H2 Database are two popular database management systems that have several key differences. Below are the six main differences between DuckDB and H2 Database:

1. Performance: DuckDB is known for its exceptional performance, especially for analytical queries. It is specifically designed to optimize read-heavy workloads and achieve faster query execution times compared to H2 Database, which is a more general-purpose database engine.

2. Memory Usage: DuckDB is designed to efficiently use memory resources, making it suitable for memory-constrained environments. It leverages techniques like vectorized query execution and adaptive caching to minimize memory footprint. On the other hand, H2 Database is a more memory-intensive system, making it better suited for applications with ample memory resources.

3. Columnar Storage: DuckDB employs a columnar storage layout by default, which offers advantages for many analytical workloads. It enables efficient compression, faster scanning, and better vectorized query execution. In contrast, H2 Database primarily uses a row-based storage layout, which provides benefits for transaction processing workloads with frequent read and write operations.

4. Database Size Limitations: DuckDB does not have any inherent limitations on database size, allowing users to handle large datasets seamlessly. On the contrary, H2 Database imposes a maximum database size limit, usually dependent on the file system or configuration settings. This limitation can be a factor to consider when handling significant amounts of data.

5. SQL Compatibility: H2 Database aims for high compatibility with the SQL standard, which makes it more versatile and compatible with various SQL-based applications and tools. DuckDB focuses on ANSI SQL compatibility, but certain advanced SQL features may not be fully supported.

6. Administration and Tooling: H2 Database provides a wide range of administration tools and options, including a web-based console, automatic backups, and easy integration with external tooling. DuckDB, being a more specialized analytical engine, currently has a more limited set of administration tools and might require additional tooling or integrations for specific management tasks.

In summary, DuckDB differentiates itself from H2 Database through its exceptional performance, efficient memory usage, columnar storage default, lack of database size limitations, specific SQL compatibility, and distinct administration and tooling options.

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Detailed Comparison

H2 Database
H2 Database
DuckDB
DuckDB

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

It is an embedded database designed to execute analytical SQL queries fast while embedded in another process. It is designed to be easy to install and easy to use. DuckDB has no external dependencies. It has bindings for C/C++, Python and R.

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Embedded database; Designed to execute analytical SQL queries fast; No external dependencies
Statistics
Stacks
1.3K
Stacks
49
Followers
121
Followers
60
Votes
0
Votes
0
Integrations
No integrations available
Python
Python
C++
C++
R Language
R Language

What are some alternatives to H2 Database, DuckDB?

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.

Microsoft SQL Server

Microsoft SQL Server

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

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.

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