Best Data Management Software for AWS Glue

Around 25 million engineers work across dozens of distinct functions. Engineers are using New Relic as every company is becoming a software company to gather real-time insight and trending data on the performance of their software. This allows them to be more resilient and provide exceptional customer experiences. New Relic is the only platform that offers an all-in one solution. New Relic offers customers a secure cloud for all metrics and events, powerful full-stack analytics tools, and simple, transparent pricing based on usage. New Relic also has curated the largest open source ecosystem in the industry, making it simple for engineers to get started using observability.

Amazon Relational Database Service (Amazon RDS), makes it easy to create, manage, and scale a cloud-based relational database. It offers a cost-efficient, resizable storage capacity and automates time-consuming admin tasks like database setup, patching, backups, and hardware provisioning. It allows you to concentrate on your applications, so they can provide the high performance, security, compatibility, and high availability that they require. Amazon RDS can be used on several database instance types, optimized for memory, performance, or I/O. It offers six familiar database engines to choose, including PostgreSQL and MySQL, MariaDB, Oracle Database and SQL Server. To easily replicate or migrate your existing databases to Amazon RDS, you can use the AWS Database Migration Service.

Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud, that combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is five times faster that standard MySQL databases and three time faster than standard PostgreSQL database. It offers the same security, availability, reliability, and cost-effectiveness as commercial databases, but at a fraction of the cost. Amazon Aurora is fully managed and maintained by Amazon Relational Database Service, (RDS). This automates tedious administration tasks such as hardware provisioning, database setup, patching and backups. Amazon Aurora is a distributed, fault-tolerant and self-healing storage that auto-scales up 64TB per database instance. It offers high availability and performance with up to 15 low latency read replicas, point in time recovery, continuous backup to Amazon S3, replication across threeAvailability Zones, and continuous backup to Amazon S3.

Amazon Redshift is preferred by more customers than any other cloud data storage. Redshift powers analytic workloads for Fortune 500 companies and startups, as well as everything in between. Redshift has helped Lyft grow from a startup to multi-billion-dollar enterprises. It's easier than any other data warehouse to gain new insights from all of your data. Redshift allows you to query petabytes (or more) of structured and semi-structured information across your operational database, data warehouse, and data lake using standard SQL. Redshift allows you to save your queries to your S3 database using open formats such as Apache Parquet. This allows you to further analyze other analytics services like Amazon EMR and Amazon Athena. Redshift is the fastest cloud data warehouse in the world and it gets faster each year. The new RA3 instances can be used for performance-intensive workloads to achieve up to 3x the performance compared to any cloud data warehouse.

Our platform allows businesses to use data, including its application in advanced analysis, machine learning and AI, to do great things without worrying that customers, employees or intellectual property are at risk. The Protegrity Data Protection Platform does more than just protect data. It also classifies and discovers data, while protecting it. It is impossible to protect data you don't already know about. Our platform first categorizes data, allowing users the ability to classify the type of data that is most commonly in the public domain. Once those classifications are established, the platform uses machine learning algorithms to find that type of data. The platform uses classification and discovery to find the data that must be protected. The platform protects data behind many operational systems that are essential to business operations. It also provides privacy options such as tokenizing, encryption, and privacy methods.

CData Connect Real-time operational and business data is critical for your organization to provide actionable insights and drive growth. CData Connect is the missing piece in your data value chain. CData Connect allows direct connectivity to any application that supports standard database connectivity. This includes popular cloud BI/ETL applications such as: - Amazon Glue - Amazon QuickSight Domo - Google Apps Script - Google Cloud Data Flow - Google Cloud Data Studio - Looker - Microsoft Power Apps - Microsoft Power Query - MicroStrategy Cloud - Qlik Sense Cloud - SAP Analytics Cloud SAS Cloud SAS Viya - Tableau Online ... and many other things! CData Connect acts as a data gateway by translating SQL and securely proxying API calls.

Progress DataDirect is passionate about empowering applications with enterprise data. We offer cloud and on-premises connectivity solutions for relational, NoSQL and Big Data data sources. We design solutions for thousands of companies and top vendors in analytics, data management, and BI. Our high-value connectors are designed to reduce development costs for a variety data sources. For greater security and peace of mind, you can get 24/7 support from experts around the world. For faster SQL access, connect with easy-to-use and time-saving drivers. Our mission is to keep up with the changing trends in data connectivity. If we don't have the connector you need, we will help you design it. Integrate connectivity into an application or service.

In just 15 minutes, you can set up your automated data catalogue and receive column-level lines, Entity Relationship diagrams, and auto-populated documentation in 24 hours. You can easily tag, find, and add documentation to data so everyone can find the right one for them. Select Star automatically detects your column-level data lineage and displays it. Now you can trust the data by knowing where it came. Select Star automatically displays how your company uses data. This allows you to identify relevant data fields without having to ask anyone else. Select Star ensures that your data is protected with AICPA SOC2 Security, Confidentiality and Availability standards.

Secoda AI can help you generate documentation and queries from your metadata. This will save your team hundreds of hours of tedious work. Secoda AI will also generate documentation and queries based on your metadata. This will save your team hundreds of tedious hours and redundant data requests. Search across all columns, dashboards and metrics, as well as tables, dashboards and tables. AI-powered searches allow you to ask any question and receive a contextual response quickly. Answer questions. Our API allows you to integrate data discovery into your workflow, without disrupting the flow. Perform bulk updates, tag PII, manage tech debt and more. Eliminate manual errors and have complete trust in your knowledge base.

Amazon Security Lake centralizes all security data, including data from AWS, SaaS, on-premises and cloud sources, into a data lake that is stored in your account. Security Lake allows you to gain a better understanding of all your security data throughout your organization. You can also improve your workloads, apps, and data. Security Lake has adopted an open standard, the Open Cybersecurity Schema Framework. The service can combine and normalize security data from AWS as well as a wide range of enterprise data sources with OCSF support. You can use your favorite analytics tools to analyze security data, while maintaining complete control and ownership of that data. Centralize data visibility across all your accounts and AWS regions. Normalizing your security data according to an open standard will streamline your data management.

Multi-cloud data security with a single pane of glass Industry's first SaaS access governance solution. Cloud is fragmented and data is scattered across different systems. Sensitive data is difficult to access and control due to limited visibility. Complex data onboarding hinders data scientist productivity. Data governance across services can be manual and fragmented. It can be time-consuming to securely move data to the cloud. Maximize visibility and assess the risk of sensitive data distributed across multiple cloud service providers. One system that enables you to manage multiple cloud services' data policies in a single place. Support RTBF, GDPR and other compliance requests across multiple cloud service providers. Securely move data to the cloud and enable Apache Ranger compliance policies. It is easier and quicker to transform sensitive data across multiple cloud databases and analytical platforms using one integrated system.

Open source data governance suite to manage data lakes and databases. Tokern is an easy-to-use toolkit for collecting, organizing and analysing metadata from data lakes. Runs as a command-line application for quick tasks. Run as a service to continuously collect metadata. Use reporting dashboards to analyze lineage, access control, and PII data. Or programmatically in Jupyter notebooks. Tokern is an open-source data governance suite for data lakes and databases. You can improve the ROI of your data, comply to regulations like HIPAA, CCPA, and GDPR, and protect your data from insider threats with confidence. Centralized metadata management for users, jobs, and datasets. Other data governance features are powered by this feature. Track column-level data lineage for Snowflake and AWS Redshift. You can build lineage using query history or ETL scripts. Interactive graphs and programming with APIs and SDKs allow you to explore lineage.

We have created a revolutionary platform for big data that collects all information about a business and provides a single source to make informed decisions. Each music business has hundreds upon hundreds of data sources. They are scattered and siloed. Our platform connects them to create a foundation of high-quality data that can be used in all aspects of music business operations. Record labels and agencies need a sophisticated data management system and governance system to ensure that their data is always available, relevant, and easily accessible. This will allow them to work efficiently and securely, as well as uncover valuable insights that no one else can. Machine learning is used to tag data as they are added to Wavo's Big Data Platform. This makes it easy to drill-down and access important information. This allows everyone in a music industry to activate and deliver business-ready data that is backed up and organized for immediate benefit.

The Alex Platform is your company's single source for data and business truth. Alex is the foundation of our customers' data-driven success. Alex is designed to reduce complexity and create value from the first day of implementation. Alex Augmented Data Catalog uses the best machine learning in the industry to quickly provide an enterprise-wide, unified data platform. Alex Data Lineage can help you understand and map your data flows, no matter how complex or complicated your technical landscape. Global teams require global coordination. The Alex Intelligent Business Glossary's beautiful interface and rich functionality are ideal for global collaboration. Unifying all definitions, policies and metrics to reduce complexity in multi-cloud environments and global enterprises will help you to manage the complexity. Global data governance programs can be powered.

For your analysis and modeling, discover and trust data. Breaking down silos can help you be more productive. See how others are using the data to get context. A simple text search can be used to find data within your organization. A PageRank-inspired search algorithm suggests results based upon names, descriptions, tags and querying/viewing activity at the table/dashboard. Automated and curated metadata, descriptions and columns of tables and columns, other frequent users, the date the table was last updated, statistics and a preview of data, can help build trust in data. Easy triage by linking ETL job and the code that generated the data. Update tables and columns with descriptions to reduce back-and-forth about which table to use or what a column contains. Find out what data coworkers use, own, or have saved. You can see dashboards created on a table to show you the most common queries.

Varada's adaptive and dynamic big data indexing solution allows you to balance cost and performance with zero data-ops. Varada's big data indexing technology is a smart acceleration layer for your data lake. It remains the single source and truth and runs in the customer's cloud environment (VPC). Varada allows data teams to democratize data. It allows them to operationalize the entire data lake and ensures interactive performance without the need for data to be moved, modelled, or manually optimized. Our ability to dynamically and automatically index relevant data at the source structure and granularity is our secret sauce. Varada allows any query to meet constantly changing performance and concurrency requirements of users and analytics API calls. It also keeps costs predictable and under control. The platform automatically determines which queries to speed up and which data to index. Varada adjusts the cluster elastically to meet demand and optimize performance and cost.

No more data catalog ghost cities. Acryl Cloud accelerates time-to-value for data producers through Shift Left practices and an intuitive user interface for data consumers. Continuously detect data-quality incidents in real time, automate anomaly detecting to prevent breakdowns, and drive quick resolution when they occur. Acryl Cloud supports both pull-based and push-based metadata ingestion to ensure information is reliable, current, and definitive. Data should be operational. Automated Metadata Tests can be used to uncover new insights and areas for improvement. They go beyond simple visibility. Reduce confusion and speed up resolution with clear asset ownership and automatic detection. Streamlined alerts and time-based traceability are also available.