Does my data leave the premises?

No, Acceldata observes your data inline so it is highly scalable and secure.

What types of data can you manage?

We observe structured, unstructured and streaming datasets.

Do you provide recommendations?

Yes, we provide recommendations on data quality rules to use based on the data context and several others.

Do you support on-prem and cloud data?

Yes, we can observe data that’s on premises and in the cloud. This makes us ideally suited for cloud migration initiatives.

Can I customize data quality rules?

Yes, you can customize data quality rules and specify exactly where they apply.

Fine grained RBAC, each feature of ADOC can be accessed by users only if they have the required permissions. RBAC also extends to applicable API operations.

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Collibra vs Acceldata

Data Observability Product Capability Comparison

Explore Acceldata

Data on-premises, Data in the Cloud, various data types

Data observability for both on-prem and cloud deployments, allowing flexibility for customers

Data observability regardless of location
Structured & unstructured data + files
Streaming data (Kafka, in production 1+ years)
Adapts to your data ecosystem design

Collibra provides data quality for on premise and cloud data sources.

Data observability for on premise and cloud
Structured & unstructured data + files
Streaming data (Kafka, Mar 2024)
Flexible data ecosystem design

Observability for repositories, pipelines, compute, and usage across all zones. 5 Pillars of data observability as defined by Gartner

Supports all 5 pillars of data observability as defined by Gartner

Data, data pipelines, infrastructure and compute, cost, usage/users
Landing zone, enrichment zone, and consumption zone
Catch issues & anomalies early

Collibra observes data in your repositories via a data governance approach instead of the actual data flows through pipelines, actual queries run by users, etc.

Observability for data in sources across on-premises and cloud data sources
No observability for pipelines, usage, compute, and cost.
Identify issues at consumption zone which increases costs, time, and complexity root cause analysis

Depth and breadth of data observability coverage

Granular coverage of wide variety of metrics

Data: Data quality, data reconciliation, data lineage, data drift, schema drift, data freshness, data cadence and data anomalies.
Pipeline: Auto discovery, pipeline lineage, run status, alerts, policies
Compute: sizing, run status, warehouse/cluster optimization, query optimization, query fingerprinting, Data partitioning and clustering optimization, best practice enforcement
Users: Workload usage, alerts, recommendations
Cost: Spend by org unit, query level spend, chargebacks, forecasting

Collibra only looks at the data that is part of your cloud data warehouse and the queries against the cloud data warehouse.

Data: behavior, schema, shape, and custom monitors
Pipeline: Indirect monitoring of data pipeline infrastructure
Compute: Not available
Users: Not available
Cost: Not available

Ability to create, run, and manage data checks on-prem and cloud needed for enterprise scale

Architected and field-tested to support the scale of large enterprises.

Distributed architecture for parallel execution and capacity across entire data landscape
Policy execution decoupled from the data
Shift left of quality rules detect issues at source
Field proven policy capacity and performance at exabyte scale

Collibra data checks are based around SQL rules limiting its ability to data stored in neat tables

Distributed architecture for parallel execution and capacity
Policy execution decoupled from the data
Limited shift left capabilities
Push down and pull up policy capabilities

Create sophisticated custom business rules and policies

Business and regulatory requirements can be highly complex and disparate, having the full flexibility of programming code simplifies compliance

Create policies using OOTB rules or custom SQL
Create complex logic and checks with standard coding languages (Python, Scala, Java, JavaScript)

Policy reuse and usage analytics

Collibra is unable to create rules and policies leveraging the full power of code.

Create policies using OOTB rules or custom SQL
No ability to create rules using coding languages
Policy templates are available

Automatic recommendations for data policy assignments and enforcement

Acceldata provides automatic recommendations for data rules and policies to quickly increase your data quality.

Model based engine recommends policies based on data profiling
Identifies gaps for remediation based on similar fields in multiple datasets
Continuous AI/ML learning engine based on profiles, rules library and derived auto-tags.
Optional human in the loop guardrails and approvals for AI/ML recommendation and rules

Automatic policies are data behavior, schema, and shape.

Automatically assigns policy for data behavior, schema and shape
Unavailable
May detect data changes but limited actions beyond alerts.
Basic human in the loop limited to approve/reject actions

Visual data lineage and deep metrics at each hop to identify data problem source and causes

Complete data lineage and instrumentation enables easy and quick identification of the root cause of data problems. Lineage and observability metrics include:

Monitors files, databases, clusters, warehouses, tables, and columns
On-premises and cloud data sources
Full data tracking from landing through consumption

Collibra Data Quality does not have data lineage. Must purchase the Collibra Data Lineage product as an add on.
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Observability into the behavior, performance, and reliability of the data and infrastructure pipeline

Acceldata sees and tracks the full data and infrastructure pipeline lineage across the data landscape (landing, enrichment, consumption) for both on-premise and cloud. Ensuring fresh, complete and timely data for business decisions.

pipeline-metrics: efficiency, uptime/downtime, throughput, task error rate, resource utilization,
Infrastructure metrics:: Latency, error rates, data loss, HW utilization, queue length

Tracks the data performance but missing infrastructure attributes.

No true pipeline metrics. Only supports data rules, behavior, schema, outliers, dupes, shapes, patterns, and records
No infrastructure metrics

Alert, quarantine, and circuit breaker policies isolate bad data and prevent downstream impacts

Get better data quality from the start with lineage and trace back from the data warehouse to the entry of data (landing zone). Automatically detect and root cause issues before they get expensive and time consuming to fix.

Real-time Alert, notifications, and throttling (noise)
Quarantine Policy
Circuit Breaker

Shift left capabilities will alert, but there are no methods to stop the bad data

Notifications in product and email
No data quarantine policy
No circuit breaker

Notification of cost and performance anomalies for both queries and infrastructure

Acceldata provides deep detailed understanding and visibility into the cost and performance of the query down to the infrastructure level. It includes maintaining historical query and budgetary trend data that can even factor in seasonality.

Identify and optimize long-running or inefficient queries
Identify similar poorly written queries
Find unused clusters, tables and warehouses etc.
Isolate waste from unneeded queries
Under-provisioned infrastructure

There is no budgeting or cost capabilities.

Provide automatic recommendations for query and infrastructure sizing and performance optimizations

Acceldata looks across queries and provides recommendations for optimizing queries and the underlying infrastructure.

Recommendations for right sizing cloud data warehouse and data lakehouse
AI based SQL query optimization
Codify best practices from Snowflake and Databricks, prevents best practice drift

There are no recommendations for sizing or performance optimizations

Monitor and analyze data warehouse cost including show back, charge back, and budgeting

Maintains historical spend rates across queries, teams, and tracks spends to budget allocations providing full spectrum visibility. Enables FinOps with show back and chargeback capabilities.

Directly tracks and reports spend and budget
Query show back and charge back

No budgeting or cost capabilities.

Recommended rules and policies including AI based recommendations

Acceldata understands your data elements and automatically recommends rules and policies for use.

Leverages AI profiling to learn what is “normal” and create rules for data set.

Recommended root cause analysis

Acceldata provides detailed end to end alerting across the data ecosystem, infrastructure, and data zones. This speeds root cause analysis.

Not available

GenAI assisted rules

GenAI translates natural language inputs into data quality rules

Collibra AdaptiveRules automatically observes and generates alerts based on numeric changes over time.

AI assisted data freshness and completeness recommendations

AI supplemented Copilot streamlines validations against data tables and recommends new policy settings for use

AI assisted freshness and volume detectors

Integrations - Cloud data sources

Acceldata integrates into the standard cloud data sources including Snowflake, Databricks, Athena, S3, etc

Integrates with cloud data warehouses like Snowflake and Databricks.

Integrations - On-premises data sources

Acceldata integrates into many of the the standard on-premises data sources including: Oracle, MySQL, SAP HANA, MongoDB, HDFS and more.

Integrates into many on-premises data sources.

On-premises data sources
No Kafka

Security Certifications & Secure Data

Acceldata meets various regulatory compliance and certification requirements including SOC-2 Type 2 and ISO 27001. The product regularly undergoes security and penetration testing.

SOC 2 Type 2
ISO 27001
HIPAA, GDPR, CCPA

Enterprise scale and performance

Acceldata is operating at Petabyte data scale, 1000s daily rule runs, 100+ million record assets

Acceldata is operating at Petabyte data scale, 1000s daily rule runs, 100+ million record assets.
Runs and policy runs do not affect the data warehouse

No public available information about policy capacity or data size..

Governance Meets Operational Excellence

Tightly-Coupled Integration
for Maximum Impact

Collibra Delivers
Governance

Acceldata ADOC
Delivers Operations

Together They
Deliver Excellence

Comparative Value Analysis

Why Leading Enterprises Choose Both

Customer Success Story

Seamless Integration, Powerful Results

Our users love us

Frequently Asked Questions (FAQs)

Collibra vs Acceldata

Ready to get started

Expert-led Demos

30-Day Free Trial

Meet with Us

Products

Governance Meets Operational Excellence

Tightly-Coupled Integration for Maximum Impact

Collibra Delivers Governance

Acceldata ADOC Delivers Operations

Together They Deliver Excellence

Comparative Value Analysis

Why Leading Enterprises Choose Both

Customer Success Story

Seamless Integration, Powerful Results

Our users love us

Frequently Asked Questions (FAQs)

Collibra vs Acceldata

Ready to get started

Expert-led Demos

30-Day Free Trial

Meet with Us

Tightly-Coupled Integration
for Maximum Impact

Collibra Delivers
Governance

Acceldata ADOC
Delivers Operations

Together They
Deliver Excellence