Best Database Software for Flyte

Find and compare the best Database software for Flyte in 2024

Use the comparison tool below to compare the top Database software for Flyte on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Google Cloud Platform Reviews
    Top Pick

    Google Cloud Platform

    Google

    Free ($300 in free credits)
    54,574 Ratings
    See Software
    Learn More
    Google Cloud is an online service that lets you create everything from simple websites to complex apps for businesses of any size. Customers who are new to the system will receive $300 in credits for testing, deploying, and running workloads. Customers can use up to 25+ products free of charge. Use Google's core data analytics and machine learning. All enterprises can use it. It is secure and fully featured. Use big data to build better products and find answers faster. You can grow from prototypes to production and even to planet-scale without worrying about reliability, capacity or performance. Virtual machines with proven performance/price advantages, to a fully-managed app development platform. High performance, scalable, resilient object storage and databases. Google's private fibre network offers the latest software-defined networking solutions. Fully managed data warehousing and data exploration, Hadoop/Spark and messaging.
  • 2
    Snowflake Reviews

    Snowflake

    Snowflake

    $40.00 per month
    4 Ratings
    Your cloud data platform. Access to any data you need with unlimited scalability. All your data is available to you, with the near-infinite performance and concurrency required by your organization. You can seamlessly share and consume shared data across your organization to collaborate and solve your most difficult business problems. You can increase productivity and reduce time to value by collaborating with data professionals to quickly deliver integrated data solutions from any location in your organization. Our technology partners and system integrators can help you deploy Snowflake to your success, no matter if you are moving data into Snowflake.
  • 3
    Amazon Athena Reviews
    Amazon Athena allows you to easily analyze data in Amazon S3 with standard SQL. Athena is serverless so there is no infrastructure to maintain and you only pay for the queries you run. Athena is simple to use. Simply point to your data in Amazon S3 and define the schema. Then, you can query standard SQL. Most results are delivered in a matter of seconds. Athena makes it easy to prepare your data for analysis without the need for complicated ETL jobs. Anyone with SQL skills can quickly analyze large-scale data sets. Athena integrates with AWS Glue Data Catalog out-of-the box. This allows you to create a unified metadata repositorie across multiple services, crawl data sources and discover schemas. You can also populate your Catalog by adding new and modified partition and table definitions. Schema versioning is possible.
  • 4
    Dolt Reviews

    Dolt

    DoltHub

    $50 per month
    Git can be used to control your SQL database tables. Commit, branch merge, clone pull and push your data. Use a familiar user interface to explore data and history based on time, commit, tag, branch or clone. Dolt fixes this problem by adding a special replica to an existing MySQL deployment. No migration is needed. You can get an audit log for every cell, branch, time travel and time travel on a copy.
  • 5
    SQLAlchemy Reviews
    SQLAlchemy, the Python SQL toolkit and the object-relational mapping program that gives developers the full power of SQL, is SQLAlchemy. SQL databases behave less as object collections when performance and size start to matter. Object collections behave less like rows and tables the more abstraction starts mattering. SQLAlchemy is designed to accommodate both these principles. SQLAlchemy views the database as a relational algebra engine and not just a collection table. Rows can be selected not only from tables, but also joins or select statements. Any of these units can be combined into a larger structure. This idea is the basis of SQLAlchemy’s expression language. SQLAlchemy's object-relational mappingper (ORM) is the most well-known component. This optional component provides the data mapper pattern.
  • 6
    DuckDB Reviews
    Processing and storage of tabular datasets, e.g. CSV or Parquet files. Large result set transfer to client. Large client/server installations are required for central enterprise data warehousing. Multiple concurrent processes can be used to write to a single database. DuckDB is a relational database management software (RDBMS). It is a system to manage data stored in relational databases. A relation is basically a mathematical term for a particular table. Each table is a named collection. Each row in a table has the same number of named columns. Each column is of a particular data type. Schemas are used to store tables, and a collection can be accessed to access the entire database.
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