Best Data Management Software for Kylo

Elastic is a search company. Elasticsearch, Kibana Beats, Logstash, and Elasticsearch are the founders of the ElasticStack. These SaaS offerings allow data to be used in real-time and at scale for analytics, security, search, logging, security, and search. Elastic has over 100,000 members in 45 countries. Elastic's products have been downloaded more than 400 million times since their initial release. Today, thousands of organizations including Cisco, eBay and Dell, Goldman Sachs and Groupon, HP and Microsoft, as well as Netflix, Uber, Verizon and Yelp use Elastic Stack and Elastic Cloud to power mission critical systems that generate new revenue opportunities and huge cost savings. Elastic is headquartered in Amsterdam, The Netherlands and Mountain View, California. It has more than 1,000 employees in over 35 countries.

MySQL is the most widely used open-source database in the world. MySQL is the most popular open source database for web-based applications. It has been proven to be reliable, performant, and easy-to-use. This database is used by many high-profile web properties, including Facebook, Twitter and YouTube. It is also a popular choice for embedded databases, distributed by thousands ISVs and OEMs.

Bipp's cloud BI platform is powered by the bippLang Data modeling language. It was created for SQL and data analysts right from the beginning. It saves time for you and your team so that your business can make faster, better-informed decisions. BippLang data modeling language simplifies SQL queries by creating complex data models with custom columns, dynamic sub-querying, and reusable data. Git-based version control allows analysts to collaborate; all data models are automatically backed by the system. An always-free version allows you to access a powerful BI platform and professional support at no additional cost. In-database analytics makes it easy to access the data in a single system. This speeds up access and produces real-time results. Auto-SQL generator uses joins in the data model to determine which tables to join, and generate dynamic sub-queries based upon context. Data models that are single source of truth ensure that everyone in the organization can base business decisions on the same data.

In seconds, anyone can find hidden insights in their company data. Search your data to find insights and automated insights. ThoughtSpot allows anyone to ask any question, find insights, drill infinitely into company data in seconds. You don't need to wait for custom reports from data specialists. Now you can instantly answer any data questions that arise. You empower non-technical employees to answer their data questions while you create a single source for truth with security, governance and scale. Maximize your cloud data warehouse's value and speed up the speed-to-insight process for everyone in your company. Access to insights is now possible in just minutes. This will transform the way you use data. Learn how ThoughtSpot helps organizations get more value out of their data. You can deploy as software or SaaS in your virtual private clouds. AI-driven insights to help you make better decisions sooner.

Quickly prepare data to provide trusted insights across the organization. Business analysts and data scientists spend too much time cleaning out data rather than analyzing it. Talend Data Preparation is a self-service, browser-based tool that allows you to quickly identify errors and create rules that can be reused and shared across large data sets. With our intuitive user interface and self-service data preparation/curation functionality, anyone can perform data profiling, cleansing, enriching and enrichment in real time. Users can share prepared datasets and curated data, and embed data preparations in batch, bulk, or live data integration scenarios. Talend allows you to transform ad-hoc analysis and data enrichment jobs into fully managed, reusable process. You can use any data source, including Teradata and AWS, Salesforce and Marketo, to operationalize data preparation. Always using the most recent datasets. Talend Data Preparation gives you control over data governance.

The BiG EVAL platform provides powerful software tools to ensure and improve data quality throughout the entire lifecycle of information. BiG EVAL's data quality and testing software tools are built on the BiG EVAL platform, a comprehensive code base that aims to provide high performance and high flexibility data validation. All features were developed through practical experience gained from working with customers. It is crucial to ensure high data quality throughout the data lifecycle. This is essential for data governance. BiG EVAL DQM, an automation solution, supports you in all aspects of data quality management. Continuous quality checks validate enterprise data, provide a quality indicator, and support you in solving quality problems. BiG EVAL DTA allows you to automate testing tasks within your data-oriented project.

Apache Hadoop is a software library that allows distributed processing of large data sets across multiple computers. It uses simple programming models. It can scale from one server to thousands of machines and offer local computations and storage. Instead of relying on hardware to provide high-availability, it is designed to detect and manage failures at the application layer. This allows for highly-available services on top of a cluster computers that may be susceptible to failures.

Apache Spark™, a unified analytics engine that can handle large-scale data processing, is available. Apache Spark delivers high performance for streaming and batch data. It uses a state of the art DAG scheduler, query optimizer, as well as a physical execution engine. Spark has over 80 high-level operators, making it easy to create parallel apps. You can also use it interactively via the Scala, Python and R SQL shells. Spark powers a number of libraries, including SQL and DataFrames and MLlib for machine-learning, GraphX and Spark Streaming. These libraries can be combined seamlessly in one application. Spark can run on Hadoop, Apache Mesos and Kubernetes. It can also be used standalone or in the cloud. It can access a variety of data sources. Spark can be run in standalone cluster mode on EC2, Hadoop YARN and Mesos. Access data in HDFS and Alluxio.