Acceldata

aid: acceldata
url: >-
  https://raw.githubusercontent.com/api-evangelist/acceldata/refs/heads/main/apis.yml
name: Acceldata
type: Index
image: https://kinlane-productions.s3.amazonaws.com/apis-json/apis-json-logo.jpg
tags:
  - AI Agents
  - Data Management
  - Data Observability
  - Data Pipeline
  - Data Quality
  - Intelligence
  - Observability
description: >-
  Acceldata is an agentic data management platform that helps enterprises
  monitor, govern, and optimize data across cloud, lakehouse, and hybrid
  environments. The platform combines AI-powered agents with data observability
  to proactively detect issues, trace root causes, and automate remediation
  workflows. Key products include ADM (Agentic Data Management), ADOC
  (Acceldata Data Observability Cloud), Pulse for Hadoop environments, and
  Agent Studio for building custom AI agents. It supports integrations with
  Snowflake, Databricks, AWS, GCP, Azure, and Hadoop.
created: '2025-02-24'
modified: '2026-04-19'
specificationVersion: '0.19'
apis:
  - aid: acceldata:adoc-api
    name: Acceldata Data Observability Cloud API
    description: >-
      The ADOC API provides programmatic access to data observability features
      including alerts, data quality rules, pipeline monitoring, data lineage,
      users, groups, roles, and permissions within the Acceldata Data
      Observability Cloud platform.
    humanURL: https://docs.acceldata.io/api/introduction
    baseURL: https://api.acceldata.app/v1
    tags:
    - Data Observability
    - Data Quality
    - Alerts
    - Data Pipeline
    properties:
    - url: https://docs.acceldata.io/api/introduction
      type: Documentation
    - url: https://docs.acceldata.io/api/authentication
      type: Authentication
    - url: openapi/acceldata-adoc-api.yaml
      type: OpenAPI
    - url: json-schema/adoc-api-alert-schema.json
      type: JSONSchema
    - url: json-schema/adoc-api-alert-list-schema.json
      type: JSONSchema
    - url: json-schema/adoc-api-data-quality-rule-schema.json
      type: JSONSchema
    - url: json-schema/adoc-api-data-quality-rule-list-schema.json
      type: JSONSchema
    - url: json-schema/adoc-api-dataset-schema.json
      type: JSONSchema
    - url: json-schema/adoc-api-dataset-list-schema.json
      type: JSONSchema
    - url: json-schema/adoc-api-lineage-node-schema.json
      type: JSONSchema
    - url: json-schema/adoc-api-lineage-graph-schema.json
      type: JSONSchema
    - url: json-schema/adoc-api-pipeline-job-schema.json
      type: JSONSchema
    - url: json-schema/adoc-api-pipeline-job-list-schema.json
      type: JSONSchema
    - url: json-schema/adoc-api-user-schema.json
      type: JSONSchema
    - url: json-schema/adoc-api-user-list-schema.json
      type: JSONSchema
    - url: json-schema/adoc-api-role-schema.json
      type: JSONSchema
    - url: json-schema/adoc-api-role-list-schema.json
      type: JSONSchema
    - url: json-structure/adoc-api-alert-structure.json
      type: JSONStructure
    - url: json-structure/adoc-api-alert-list-structure.json
      type: JSONStructure
    - url: json-structure/adoc-api-data-quality-rule-structure.json
      type: JSONStructure
    - url: json-structure/adoc-api-data-quality-rule-list-structure.json
      type: JSONStructure
    - url: json-structure/adoc-api-dataset-structure.json
      type: JSONStructure
    - url: json-structure/adoc-api-dataset-list-structure.json
      type: JSONStructure
    - url: json-structure/adoc-api-lineage-node-structure.json
      type: JSONStructure
    - url: json-structure/adoc-api-lineage-graph-structure.json
      type: JSONStructure
    - url: json-structure/adoc-api-pipeline-job-structure.json
      type: JSONStructure
    - url: json-structure/adoc-api-pipeline-job-list-structure.json
      type: JSONStructure
    - url: json-structure/adoc-api-user-structure.json
      type: JSONStructure
    - url: json-structure/adoc-api-user-list-structure.json
      type: JSONStructure
    - url: json-structure/adoc-api-role-structure.json
      type: JSONStructure
    - url: json-structure/adoc-api-role-list-structure.json
      type: JSONStructure
    - url: examples/adoc-api-alert-example.json
      type: Example
    - url: examples/adoc-api-alert-list-example.json
      type: Example
    - url: examples/adoc-api-data-quality-rule-example.json
      type: Example
    - url: examples/adoc-api-dataset-example.json
      type: Example
    - url: examples/adoc-api-lineage-graph-example.json
      type: Example
    - url: examples/adoc-api-pipeline-job-example.json
      type: Example
    - url: examples/adoc-api-user-example.json
      type: Example
    - url: examples/adoc-api-role-example.json
      type: Example
common:
  - type: PostmanWorkspace
    url: https://www.postman.com/kinlaneapi/acceldata/overview
  - type: ArazzoWorkflows
    url: arazzo/
    workflows:
    - url: arazzo/acceldata-access-review-workflow.yml
      name: Acceldata Access Review
      summary: List organization users and the platform roles so access can be reviewed against defined permissions.
    - url: arazzo/acceldata-create-and-verify-rule-workflow.yml
      name: Acceldata Create and Verify Data Quality Rule
      summary: Resolve a dataset, create a data quality rule on it, and confirm the rule is registered.
    - url: arazzo/acceldata-critical-alert-sweep-workflow.yml
      name: Acceldata Critical Alert Sweep
      summary: List open critical alerts and acknowledge the first one when any are present.
    - url: arazzo/acceldata-dataset-quality-audit-workflow.yml
      name: Acceldata Dataset Quality Audit
      summary: Resolve a dataset, list its data quality rules, and map its lineage for impact analysis.
    - url: arazzo/acceldata-onboard-rule-with-impact-workflow.yml
      name: Acceldata Onboard Rule With Impact
      summary: Resolve a dataset, review its existing rules, create a new rule, and map downstream impact.
    - url: arazzo/acceldata-pipeline-failure-investigation-workflow.yml
      name: Acceldata Pipeline Failure Investigation
      summary: Find failed pipeline jobs, pull related critical alerts, and acknowledge the first one.
    - url: arazzo/acceldata-triage-dataset-alerts-workflow.yml
      name: Acceldata Triage Dataset Alerts
      summary: Resolve a dataset, pull its open alerts, and acknowledge the most severe one.
  - type: GitHubOrganization
    url: https://github.com/acceldata-io
  - type: LinkedIn
    url: https://www.linkedin.com/company/acceldata
  - type: Website
    url: https://www.acceldata.io/
  - type: Portal
    url: https://accounts.acceldata.app/login
  - type: Documentation
    url: https://docs.acceldata.io/
  - type: GettingStarted
    url: https://docs.acceldata.io/api/introduction
  - type: Pricing
    url: https://www.acceldata.io/pricing
  - type: Blog
    url: https://www.acceldata.io/blog
  - type: PrivacyPolicy
    url: https://www.acceldata.io/privacy-policy
  - type: TermsOfService
    url: https://www.acceldata.io/terms-of-use
  - type: Features
    data:
    - name: Agentic Data Management
      description: AI-powered agents that proactively detect issues, trace root 
        causes, and automate data quality remediation workflows
    - name: Data Quality Monitoring
      description: Multi-variate anomaly detection, column-level profiling, and 
        proactive monitoring across all data platforms
    - name: Data Lineage
      description: End-to-end data lineage visualization with schema change 
        management and column-level impact analysis
    - name: Pipeline Health Monitoring
      description: Real-time SLA monitoring, bottleneck identification, and root 
        cause analysis for data pipelines
    - name: Data Cost Management
      description: Visibility into data spending, budget optimization, 
        chargebacks, and cost forecasting across cloud environments
    - name: Business Notebook
      description: Natural language interface with contextual memory for querying 
        data quality and observability insights
    - name: Agent Studio
      description: Low-code environment for building and deploying custom AI 
        agents for data management workflows
    - name: BYOLLM Support
      description: Bring Your Own Large Language Model for enterprise-controlled 
        AI inference within data operations
    - name: xLake Reasoning Engine
      description: Exabyte-scale, AI-aware processing engine supporting cloud 
        hyperscalers and on-premises deployments
  - type: UseCases
    data:
    - name: Data Quality Assurance
      description: Continuously monitor and automatically remediate data quality 
        issues across cloud and hybrid environments
    - name: Cloud Migration Validation
      description: Validate data completeness, consistency, and accuracy during 
        cloud migration projects
    - name: AI and LLM Data Readiness
      description: Ensure data pipelines produce clean, reliable, and AI-ready 
        datasets for training and inference
    - name: Cost Optimization and FinOps
      description: Identify and reduce wasteful data pipeline and infrastructure 
        costs with granular usage analytics
    - name: Data Reconciliation
      description: Automatically detect and resolve discrepancies between source 
        and target systems across platforms
    - name: Compliance and Data Governance
      description: Track data lineage and access patterns to support regulatory 
        compliance and data governance programs
  - type: Integrations
    data:
    - name: Snowflake
      description: Native integration for monitoring Snowflake data quality, query
        performance, and cost optimization
    - name: Databricks
      description: Integration for observing Databricks lakehouse pipelines, job 
        health, and data quality
    - name: AWS
      description: Support for AWS data services including S3, Redshift, Glue, 
        EMR, and Athena
    - name: Google Cloud Platform
      description: Integration with GCP data services including BigQuery, 
        Dataflow, and Cloud Storage
    - name: Microsoft Azure
      description: Integration with Azure Synapse, Azure Data Factory, and Azure 
        Data Lake Storage
    - name: Hadoop / Apache
      description: Dedicated Pulse product for Hadoop ecosystem monitoring 
        including HDFS, YARN, Hive, and Spark

  - url: rules/acceldata-spectral-rules.yml
    type: SpectralRules
  - url: capabilities/data-observability.yaml
    type: NaftikoCapability
  - url: vocabulary/acceldata-vocabulary.yaml
    type: Vocabulary
  - url: json-ld/acceldata-adoc-api-context.jsonld
    type: JSONLD
  - type: Integrations
    url: https://www.acceldata.io/integrations
  - type: LLMsTxt
    url: https://docs.acceldata.io/llms.txt
integrations:
  - name: Acceldata Logo blue SVG
  - name: Acceldata Logo White SVG
  - name: Acceldata as Information security management certified
  - name: Acceldata as AICPA SOC Certified
maintainers:
  - FN: Kin Lane
    email: [email protected]