Amundsen vs Vertica

Overview

Vertica

Stacks90

Followers120

Votes16

Amundsen

Stacks17

Followers42

Votes0

Amundsen vs Vertica: What are the differences?

Key Differences between Amundsen and Vertica

Data Source: Amundsen primarily serves as a metadata management tool, enabling users to discover and explore data assets within an organization. On the other hand, Vertica is a high-performance analytical database designed for handling large volumes of data and complex query processing.
Query Language: Amundsen does not have its own query language as it focuses on metadata management and discovery. In contrast, Vertica uses SQL (Structured Query Language) as its query language, allowing users to perform complex analytical queries on the data stored within the database.
Use Case: Amundsen is more suitable for data discovery, data lineage tracking, and data governance tasks within an organization. Vertica, on the other hand, is best suited for data warehousing and analytical workloads that require high-speed query processing and scalability.
Scalability: Vertica is known for its superior scalability, allowing organizations to handle massive amounts of data and queries efficiently. Amundsen, while useful for metadata management, may face limitations in handling large-scale analytics workloads due to its focus on data discovery and lineage tracking.
Integration: Vertica offers seamless integration with various BI tools, data integration platforms, and ETL tools, making it easier for organizations to incorporate the database into their existing data infrastructure. In contrast, while Amundsen provides integrations with some popular data discovery tools, its primary focus on metadata management may limit its integration capabilities for broader analytics use cases.
Cost Structure: The cost structure of Amundsen may vary depending on the deployment model, number of users, and features required for metadata management within an organization. Vertica, as a commercial analytical database, generally involves licensing fees based on the size of the data stored and the level of support required.

In Summary, Amundsen is a metadata management tool focused on data discovery, while Vertica is an analytical database designed for high-performance query processing and scalability.

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Detailed Comparison

Vertica	Amundsen
It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.	It is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.
Analyze All of Your Data. No longer move data or settle for siloed views;Achieve Scale and Performance;Fear of growing data volumes and users is a thing of the past;Future-Proof Your Analytics	Datasets (Tables) schema and usage frequency/popularity; Users bookmark, owner, frequent user; Dashboard popularity, lineage to datasets
Statistics
Stacks 90	Stacks 17
Followers 120	Followers 42
Votes 16	Votes 0
Pros & Cons
Pros 3 Shared nothing or shared everything architecture 1 Partition pruning and predicate push down on Parquet 1 Vertica is the only product which offers partition prun 1 Query-Optimized Storage 1 Fully automated Database Designer tool	No community feedback yet
Integrations
Oracle Golang MongoDB MySQL Sass Mode PowerBI Tableau Talend	Google BigQuery Snowflake AWS Glue Superset Apache Hive

What are some alternatives to Vertica, Amundsen?

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.

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 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.

Related Comparisons

Amundsen vs Vertica: What are the differences?

Key Differences between Amundsen and Vertica

Data Source: Amundsen primarily serves as a metadata management tool, enabling users to discover and explore data assets within an organization. On the other hand, Vertica is a high-performance analytical database designed for handling large volumes of data and complex query processing.
Query Language: Amundsen does not have its own query language as it focuses on metadata management and discovery. In contrast, Vertica uses SQL (Structured Query Language) as its query language, allowing users to perform complex analytical queries on the data stored within the database.
Use Case: Amundsen is more suitable for data discovery, data lineage tracking, and data governance tasks within an organization. Vertica, on the other hand, is best suited for data warehousing and analytical workloads that require high-speed query processing and scalability.
Scalability: Vertica is known for its superior scalability, allowing organizations to handle massive amounts of data and queries efficiently. Amundsen, while useful for metadata management, may face limitations in handling large-scale analytics workloads due to its focus on data discovery and lineage tracking.
Integration: Vertica offers seamless integration with various BI tools, data integration platforms, and ETL tools, making it easier for organizations to incorporate the database into their existing data infrastructure. In contrast, while Amundsen provides integrations with some popular data discovery tools, its primary focus on metadata management may limit its integration capabilities for broader analytics use cases.
Cost Structure: The cost structure of Amundsen may vary depending on the deployment model, number of users, and features required for metadata management within an organization. Vertica, as a commercial analytical database, generally involves licensing fees based on the size of the data stored and the level of support required.

In Summary, Amundsen is a metadata management tool focused on data discovery, while Vertica is an analytical database designed for high-performance query processing and scalability.

Amundsen vs Vertica

Overview

Amundsen vs Vertica: What are the differences?