Data Management: Page

18 top big data tools and technologies to know about in 2026

Numerous tools are available to use in big data applications. Here are 18 popular open source big data technologies, with details on their key features and use cases.

By Mary Pratt • Feb. 26, 2026

Real-time data streaming for AI: invest where it matters

Don't let batch processing lead to missed opportunities. Build AI systems for continuous data flows that deliver instant decisions, change outcomes and justify the cost.

By Stephen Catanzano • Feb. 25, 2026

Operational resilience is a benchmark for executive success

Operational resilience is emerging as an executive benchmark as regulations, board scrutiny and compliance mandates drive the need for measurable KPIs and accountability.

By Chris Tozzi • Feb. 25, 2026

How cyber insurance requirements reshape backup architecture

From immutable backups to air-gapped copies, these requirements reflect the growing need for organizations to prove they can recover from an incident -- or risk losing coverage.

By Sean Kerner • Feb. 24, 2026

Web data search specialist Nimble raises $47M to fuel growth

By raising funding when AI developers are dominating VC interest, the startup shows that there is a need for agents and other AI tools to include context from external sources.

By Eric Avidon • Feb. 24, 2026

New Databricks tool targets streaming data cost, complexity

With Zerobus Ingest, the vendor is providing a service that differentiates it from competitors by reducing the tools required to ingest real-time data to its lakehouse platform.

By Eric Avidon • Feb. 23, 2026

Experts share practices to overcome AI data readiness

Enterprise AI ambitions can stumble without strong data fundamentals. Here's how to pick, organize and maintain data so systems behave reliably and projects move to production.

By Mary Pratt • Feb. 20, 2026

Data and AI governance must team up for AI to succeed

AI applications won't produce reliable results -- and could create compliance and business ethics risks -- without strong data governance processes underpinning them.

By Craig Stedman • Feb. 19, 2026

How to secure sensitive data when offboarding employees

Establish a multi-phased approach that turns a risky situation into a managed process with several departments working in coordination to ensure a smooth exit.

By Kevin Beaver • Feb. 18, 2026

Streaming specialist Redpanda adds governance to AI suite

New Agentic Data Plane features enable users to create a governance layer for agents and could help the vendor differentiate itself from its closest competitors.

By Eric Avidon • Feb. 18, 2026

The future of AI depends on better data, not bigger models

AI's competitive advantage is shifting from model scale to data quality. Organizations that invest in governance and infrastructure build more reliable, defensible systems.

By Stephen Catanzano • Feb. 17, 2026

Graphwise aims to boost AI accuracy with GraphRAG launch

With standard RAG pipelines proving unreliable, the vendor's new feature uses knowledge graphs to add needed context to the data retrieval process that fuels AI outputs.

By Eric Avidon • Feb. 17, 2026

SurrealDB raises $23M, launches update to fuel agentic AI

Though funding isn't flowing as freely into data management as it once was, the startup is attracting interest by focusing on enabling customers to unify data for AI development.

By Eric Avidon • Feb. 17, 2026

How to cut data loss risks when employees leave

How an employee leaves influences what data they might take. Organizations can implement several practical methods to protect code, client information, and other assets.

By Mary Pratt • Feb. 13, 2026

What executives look for in a data quality platform

Data quality strategy now functions as a governance and risk discipline, with executives weighing metrics, ROI accountability and data trust as indicators of enterprise reliability.

By Donald Farmer • Feb. 10, 2026

Residual access failures put data at risk

Stop breaches that start with orphaned accounts. This guide identifies offboarding weak spots and gives leaders a practical checklist to close gaps fast and prove compliance.

By Kevin Beaver • Feb. 10, 2026

PII masking a differentiator for Aerospike’s NoSQL database

By adding native protection of personally identifiable information, the vendor is simplifying system administration while simultaneously pushing the NoSQL market.

By Eric Avidon • Feb. 9, 2026

Databricks launches PostgreSQL Lakebase to aid AI developers

Resulting from the $1B acquisition of Neon, the database built for AI workloads -- including separate compute and storage -- is now integrated with the vendor's broader platform.

By Eric Avidon • Feb. 5, 2026

Pentaho update aids data integration, semantic modeling

The vendor's latest platform update aims to speed, simplify and better govern workloads to help customers build a trusted foundation for AI development.

By Eric Avidon • Feb. 4, 2026

Snowflake launches new AI tools, unveils OpenAI partnership

New features such as an agent-powered code generator and automated semantic modeling simplify developing cutting-edge applications and improve the vendor's competitive standing.

By Eric Avidon • Feb. 3, 2026

9 metadata management standards that guide success

Organizations looking to implement metadata management can choose from existing standards that support archiving, sciences, finance and other digital resources.

By Donald Farmer • Feb. 2, 2026

Building a strong data analytics platform architecture

Data analytics platforms are crucial for information-driven enterprises. With the right architecture, organizations can gain meaningful insights and gain a competitive edge.

By Jeff McCormick • Jan. 30, 2026

Alteryx launches in-warehouse data prep tool for BigQuery

Live Query for BigQuery eliminates the need to move data between systems, saving customers from spending on data egress and reducing the risk of security leaks.

By Eric Avidon • Jan. 28, 2026

Modernized big data architecture a must for AI to deliver

Many enterprises put AI into production in 2025 but found their legacy data stacks stalled progress. See what it takes to modernize big data systems for better AI results.

By Mary Pratt • Jan. 27, 2026

The trust-at-speed paradox: Most data governance wasn’t built for AI

Agentic AI operates autonomously, exposing gaps in governance, data quality and accountability. Executives must address these limits to manage risk and move AI into production.

By Stephen Catanzano • Jan. 27, 2026