Looker vs Weka
Compare data AI Tools
21% Similar — based on 3 shared tags
Modern BI on Google Cloud that turns governed data into trusted dashboards explores and semantic metrics while giving teams row level control and scale.
WEKA is a high-performance data platform for AI and HPC that unifies NVMe flash, cloud object storage, and parallel file access to feed GPUs at scale with enterprise controls.
Feature Tags Comparison
Key Features
- Unified metrics layer: Define measures in LookML once and reuse across every chart and export without drift
- In place query engine: Push down to your cloud warehouse for scale while keeping governance and lineage intact
- Row level security: Apply policies so each audience sees only the records permitted by governance rules
- Versioned modeling: Develop in branches review changes and promote semantic updates with confidence
- Trust and audit: Centralize definitions schedules and lineage so decisions are traceable across quarters
- Extensibility: Embed dashboards or power data apps using APIs actions and components
- Parallel file system on NVMe for low-latency IO
- Hybrid tiering to object storage with policy control
- Kubernetes integration and scheduler friendliness
- High throughput to keep GPUs saturated
- Quotas snapshots and multi-tenant controls
- Encryption audit logs and SSO options
Use Cases
- Executive KPI portals that share one definition of revenue and retention
- Self serve exploration for sales ops and marketing under access policies
- Customer facing analytics embedded inside SaaS products
- Finance variance analysis that reuses governed dimensions across models
- Data apps that trigger actions back to CRMs or tickets from dashboards
- Partner portals that expose scoped explores for suppliers securely
- Feed multi-node training jobs with consistent throughput
- Consolidate research and production data under one namespace
- Tier datasets to object storage while keeping hot shards local
- Support MLOps pipelines that read and write at scale
- Accelerate EDA and simulation with parallel IO
- Serve inference features with predictable latency
Perfect For
data leaders analytics engineers BI developers product managers finance and operations teams who need governed definitions embedded analytics and warehouse scale
infra architects, platform engineers, and research leads who need to maximize GPU utilization and simplify AI data operations with enterprise controls
Capabilities
Semantic LookML Professional
Trusted self serve Professional
Embedded analytics Intermediate
Dev and governance Intermediate
Parallel IO Professional
Object Integration Intermediate
K8s & Schedulers Intermediate
Governance & Audit Professional
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