Apache Parquet vs Google Cloud Data Fusion
Overview
Share your Stack
Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.
CLI (Node.js)
Manual
Detailed Comparison
It is a columnar storage format available to any project in the Hadoop ecosystem, regardless of the choice of data processing framework, data model or programming language. | A fully managed, cloud-native data integration service that helps users efficiently build and manage ETL/ELT data pipelines. With a graphical interface and a broad open-source library of preconfigured connectors and transformations, and more. |
Columnar storage format;Type-specific encoding;
Pig integration;
Cascading integration;
Crunch integration;
Apache Arrow integration;
Apache Scrooge integration;Adaptive dictionary encoding;
Predicate pushdown;
Column stats | Code-free self-service;
Collaborative data engineering;
GCP-native;
Enterprise-grade security;
Integration metadata and lineage;
Seamless operations;
Comprehensive integration toolkit;
Hybrid enablement |
Statistics | |
Stacks 97 | Stacks 25 |
Followers 190 | Followers 156 |
Votes 0 | Votes 1 |
Pros & Cons | |
No community feedback yet | Pros
|
Integrations | |
What are some alternatives to Apache Parquet, Google Cloud Data Fusion?
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.
