Evaluate

Evaluate

Weigh the pros and cons of technologies, products and projects you are considering.

• Data warehouse technologies evolve as vendors look skyward

  The need for high-speed analytics and low latency are pushing data warehousing vendors to create and reinvent their platforms and, in some cases, reinvent themselves. Continue Reading

• Future of MongoDB could be brighter than other NoSQL engines

  Top NoSQL database MongoDB, once thought of as a revolution in data management, has come back to Earth some, but it still has a chance to stay ahead of competitors. Continue Reading

• How AI could save the enterprise data catalog

  Enterprise data catalogs record all the databases and files in a corporation, but sometimes it can become out of date. Advances in AI are helping minimize the problem. Continue Reading

• Data integration vs. ETL in the age of big data

  Data integration provides a consistent view of business performance across multiple data sources, though it needs to keep up with the changing needs of organizations and the big data revolution. Continue Reading

• Immuta introduces new features to Automated Data Governance

  The new updates also bring about native Hadoop distributed file system workspaces within Immuta and more ways to integrate Immuta with other applications and tools. Continue Reading

• Third-party database tools boast attractive alternatives

  For companies considering third-party database tools, this handbook provides expert advice on evaluating and deploying on-premises and cloud options from third parties.Continue Reading

• Database management tools from third parties make natives restless

  Third-party database performance tools offer attractive alternatives to management software from DBMS vendors, provided their capabilities include orchestration, governance and integration.Continue Reading

• Weighing the use of third-party database administration tools

  Database expert Chris Foot details the key reasons why DBAs should consider using third-party database administration to fill gaps left by the major database manufacturers.Continue Reading

• Data warehouse vs. data lake vs. data mart: Beyond the RDBMS

  There are many ways to store big data, but the choice of data warehouse vs. data lake vs. data mart comes down to who uses the data and how. Use this cheat sheet to compare.Continue Reading

• 10 Apache Kafka best practices for data management pros

  How can data management teams most effectively deploy and use Apache Kafka in data pipelines and streaming applications? Here are some key guidelines to follow.Continue Reading

• Data management roles: Data architect vs. data engineer, others

  Veteran data professional Michael Bowers differentiates between key data management positions, including their salaries and which ones can add the most business value.Continue Reading

• Key components of an effective data virtualization architecture

  Experts break down which elements -- both technical and nontechnical -- are most crucial to successfully deploying and managing a data virtualization architecture.Continue Reading

• Big data containers gain wider appeal in system deployments

  This handbook examines the use of Docker containers in Kubernetes clusters to run big data systems and offers insight on container deployment and management issues.Continue Reading

• Container technologies promise more agility for big data apps

  Along with the ability to provide greater agility and flexibility for big data applications, containers can play a role in IT strategy that drives real-time decision-making.Continue Reading

• Cloud database comparison: AWS, Microsoft, Google and Oracle

  IT expert Chris Foot evaluates the leading cloud databases from AWS, Google, Microsoft and Oracle based on their product offerings and migration capabilities.Continue Reading