Best Data Management Software for Presto

DbVisualizer is one of the world’s most popular database clients. Developers, analysts, and DBAs use it to advance their SQL experience with modern tools to visualize and manage their databases, schemas, objects, and table data and to auto-generate, write and optimize queries. It has extended support for 30+ of the major databases and has basic-level support for all databases that can be accessed with a JDBC driver. DbVisualizer runs on all major OSes. Free and Pro versions are available.

Access and access management today have become more complex and frustrating. strongDM redesigns access around the people who need it, making it incredibly simple and usable while ensuring total security and compliance. We call it People-First Access. End users enjoy fast, intuitive, and auditable access to the resources they need. Administrators gain precise controls, eliminating unauthorized and excessive access permissions. IT, Security, DevOps, and Compliance teams can easily answer who did what, where, and when with comprehensive audit logs. It seamlessly and securely integrates with every environment and protocol your team needs, with responsive 24/7 support.

Multi-platform database tool that is free for database administrators, analysts, developers, and anyone who needs to work with databases. All popular databases supported: MySQL, PostgreSQL SQLite, Oracle and SQLite. The format configuration editor was also added. Extra configuration for filter dialog (performance). For small fetch sizes, sort by column as fixed. Support for case-insensitive filters was added. Plaintext view now supports top/bottom dividers. Data editor was updated to fix conflicts between column names and alias names. Multiple rows were fixed by the Duplicate Row(s) command. The context menu was restored to the Edit sub-menu. Columns were auto-sized. Dictionary viewer was updated (for read-only connections). Configurable support for current/selected row highlighting was added

StarfishETL is a Cloud iPaaS solution, which gives it the unique ability to connect virtually any kind of solution to any other kind of solution as long as both of those applications have an API. This gives StarfishETL customers ultimate control over their data projects, with the ability to build more unique and scalable data connections.

Datameer is your go-to data tool for exploring, preparing, visualizing, and cataloging Snowflake insights. From exploring raw datasets to driving business decisions – an all-in-one tool.

With built-in intelligence, you can turn your customers into success stories. This includes dashboards, state-of-the art analytics and dashboards. BoldBI is a platform that was built from the ground up to be embedded. There are no compromises or shortcuts. Your application will be more complicated if you don't meet outdated requirements like "bring all of your data into our cube or data store." You can design complex systems for data integration, but you need to keep the embedded BI database store in synch with your data sources. Bold BI allows you to connect directly with hundreds of data sources as well as any data warehouse of choice. If you have a shared model, deploy single-tenant mode. Multi-tenant mode is best for isolated data models. This allows you to keep a single source of dashboards and publish to multiple tenants. Bold BI can be used in both common and unusual scenarios. Use JavaScript APIs to embed Bold BI directly into your application code.

GeoSpock DB - The space-time analytics database - allows data fusion in the connected world. GeoSpockDB is a unique cloud-native database that can be used to query for real-world applications. It can combine multiple sources of Internet of Things data to unlock their full potential, while simultaneously reducing complexity, cost, and complexity. GeoSpock DB enables data fusion and efficient storage. It also allows you to run ANSI SQL query and connect to analytics tools using JDBC/ODBC connectors. Users can perform analysis and share insights with familiar toolsets. This includes support for common BI tools such as Tableau™, Amazon QuickSight™, and Microsoft Power BI™, as well as Data Science and Machine Learning environments (including Python Notebooks or Apache Spark). The database can be integrated with internal applications as well as web services, including compatibility with open-source visualisation libraries like Cesium.js and Kepler.

BigLake is a storage platform that unifies data warehouses, lakes and allows BigQuery and open-source frameworks such as Spark to access data with fine-grained control. BigLake offers accelerated query performance across multicloud storage and open formats like Apache Iceberg. You can store one copy of your data across all data warehouses and lakes. Multi-cloud governance and fine-grained access control for distributed data. Integration with open-source analytics tools, and open data formats is seamless. You can unlock analytics on distributed data no matter where it is stored. While choosing the best open-source or cloud-native analytics tools over a single copy, you can also access analytics on distributed data. Fine-grained access control for open source engines such as Apache Spark, Presto and Trino and open formats like Parquet. BigQuery supports performant queries on data lakes. Integrates with Dataplex for management at scale, including logical organization.

Hue provides the best querying experience by combining the most intelligent autocomplete components and query editor. The tables and storage browses use your existing data catalog in a transparent way. Help users find the right data among thousands databases and document it themselves. Help users with their SQL queries, and use rich previews of links. Share directly from the editor in Slack. There are several apps, each specialized in one type of querying. Browsers are the first place to explore data sources. The editor excels at SQL queries. It has an intelligent autocomplete and risk alerts. Self-service troubleshooting is also available. Dashboards are primarily used to visualize indexed data, but they can also query SQL databases. The results of a search for specific cell values are highlighted. Hue has one of the most powerful SQL autocompletes on the planet to make your SQL editing experience as easy as possible.

StarRocks offers at least 300% more performance than other popular solutions, whether you're using a single or multiple tables. With a rich set connectors, you can ingest real-time data into StarRocks for the latest insights. A query engine that adapts your use cases. StarRocks allows you to scale your analytics easily without moving your data or rewriting SQL. StarRocks allows a rapid journey between data and insight. StarRocks is unmatched in performance and offers a unified OLAP system that covers the most common data analytics scenarios. StarRocks offers at least 300% faster performance than other popular solutions, whether you are working with one table or many. StarRocks' built-in memory-and-disk-based caching framework is specifically designed to minimize the I/O overhead of fetching data from external storage to accelerate query performance.

DataHub is a free and open-source metadata platform that streamlines data discovery, observability and governance across diverse data ecologies. It allows organizations to discover trustworthy data with experiences tailored to each user and eliminates breaking updates with detailed cross-platform, column-level lineage. DataHub gives you a complete view of your data, including its business, operational and technical context. The platform provides automated data quality checks, AI-driven anomaly identification and alerts teams when problems arise. It also centralizes incident tracking. DataHub's detailed ownership, documentation, and lineage information allows for quick issue resolution. It automates governance by classifying assets in real-time, reducing manual work with GenAI documentation, AI classification, and smart propagation. DataHub’s extensible architecture supports more than 70 native integrations.

Learn how users interact with your product and identify opportunities to help you make product decisions. Mode allows one Stitch analyst to perform the work of a full-time data team with speed, flexibility, collaboration. Create dashboards for annual revenue and then use chart visualizations quickly to identify anomalies. Share analysis with teams to create polished reports that are investor-ready. Connect your entire tech stack with Mode to identify upstream issues and improve performance. With webhooks and APIs, you can speed up team workflows. Learn how users interact with your product and identify areas for improvement. Use marketing and product data to identify weak points in your funnel, improve landing page performance, and prevent churn from happening.

Lyftrondata can help you build a governed lake, data warehouse or migrate from your old database to a modern cloud-based data warehouse. Lyftrondata makes it easy to create and manage all your data workloads from one platform. This includes automatically building your warehouse and pipeline. It's easy to share the data with ANSI SQL, BI/ML and analyze it instantly. You can increase the productivity of your data professionals while reducing your time to value. All data sets can be defined, categorized, and found in one place. These data sets can be shared with experts without coding and used to drive data-driven insights. This data sharing capability is ideal for companies who want to store their data once and share it with others. You can define a dataset, apply SQL transformations, or simply migrate your SQL data processing logic into any cloud data warehouse.

The only fully-managed cloud data lakehouse that can ingest data from all of your sources in minutes, and support all of your query engines on a large scale. All for a fraction the cost. With the ease of fully managed pipelines, you can ingest data from databases and event streams in near-real-time. You can query your data using any engine and support all of your use cases, including BI, AI/ML, real-time analytics and AI/ML. Simple usage-based pricing allows you to cut your costs by up to 50% compared with cloud data warehouses and ETL software. With a fully-managed, highly optimized cloud service, you can deploy in minutes and without any engineering overhead. Unify all your data into a single source and eliminate the need for data to be copied between data lakes and warehouses. Apache Hudi, Apache Iceberg and Delta Lake all offer omnidirectional interoperability, allowing you to choose the best table format for your needs. Configure managed pipelines quickly for database CDC and stream ingestion.

Open, hybrid data lakes for AI and analytics can be used to put your data to use, wherever it is located. Connect your data in any format and from anywhere. Access it through a shared metadata layer. By matching the right workloads to the right query engines, you can optimize workloads in terms of price and performance. Integrate natural-language semantic searching without the need for SQL to unlock AI insights faster. Manage and prepare trusted datasets to improve the accuracy and relevance of your AI applications. Use all of your data everywhere. Watsonx.data offers the speed and flexibility of a warehouse, along with special features that support AI. This allows you to scale AI and analytics throughout your business. Choose the right engines to suit your workloads. You can manage your cost, performance and capability by choosing from a variety of open engines, including Presto C++ and Spark Milvus.

lakeFS allows you to manage your data lake in the same way as your code. Parallel pipelines can be used for experimentation as well as CI/CD of your data. This simplifies the lives of data scientists, engineers, and analysts who work in data transformation. lakeFS is an open-source platform that provides resilience and manageability for object-storage-based data lakes. lakeFS allows you to build repeatable, atomic, and versioned data lakes operations. This includes complex ETL jobs as well as data science and analysis. lakeFS is compatible with AWS S3, Azure Blob Storage, and Google Cloud Storage (GCS). It is API compatible to S3 and seamlessly integrates with all modern data frameworks like Spark, Hive AWS Athena, Presto, AWS Athena, Presto, and others. lakeFS is a Git-like branching/committing model that can scale to exabytes by using S3, GCS, and Azure Blob storage.

Hudi is a rich platform for building streaming data lakes using incremental data pipelines on a self managing database layer. It can also be optimized for regular batch processing and lake engines. Hudi keeps a timeline of all actions on the table at different times. This allows for instantaneous views and efficient retrieval of data in the order they were received. The following components make up a Hudi instant. Hudi provides efficient upserts by mapping a given Hoodie key consistently with a file ID, via an indexing mechanism. Once a record is written to a file, the mapping between record key/file group/file ID never changes. The mapped file group includes all versions of a group record.

As a leader in business, you must be able to trust your data, and be 100 percent certain that they are accurate, well-governed and compliant. Include all data from all sources and all locations without limitation. Understanding your data assets. Audit your project for quality, compliance and risk. Catalogue a complete inventory of data across all data types and sources, creating a shared understanding about your data assets. Conduct a fast, accurate, and affordable audit of your data. PCI, PII and PHI audits can be completed quickly, accurately and completely. No software to buy, as a service. Measure and audit the data quality and duplication of data across all your enterprise data assets - cloud-native or on-premises. Ensure compliance with global data privacy laws at scale. Discover, classify and audit privacy compliance. Monitor PII/PCI/PHI and automate DSAR processes.