Exploring Data Observability Tools? Access the Gartner® Report to learn more.
By selecting “Accept All Cookies,” you consent to the storage of cookies on your device to improve site navigation, analyze site usage, and support our marketing initiatives. For further details, please review our Privacy Policy.

All-in-One Enterprise Data Observability

Gain Comprehensive insights into your data stack to improve data quality, pipeline reliability, platform performance, and spend efficiency.

Get Started

Gartner® Market Guide for Data Observability Tools

Access Report

How it Works

Connect Data Sources

Connects to over 70 data sources spanning your entire data stack. Automatically builds pipeline maps by reading metadata and other heuristics

Turn on Policies

Select from over 100 out of the box policies or create your own custom policies, events, and rules.

Observe & Improve

Get alerted, automate actions and continue improving your data operations to deliver complete trust in your data.

Our Customers

Acceldata Data Observability Cloud is proven in the most demanding environments. Among our customers are some of the top banks in the world, some of the top telcos in the world and the top data providers in the world.

Why are we different?

We have the most comprehensive data observability platform for the modern enterprise.


Feature rich, simple to use, addresses all your observability needs including data quality, data drift, schema drift, reconciliation, pipeline monitoring, infrastructure monitoring, FinOps, plus many more.

Shift Left Data Observability

Unlike approaches that only focus on the consumption zone, Acceldata Integrates observability into the data pipeline and data infrastructure from the initial landing zone through to consumption. Shift-left provides up to 38x reduction in the cost of bad data.

Petabyte Scale Data

Acceldata’s unique data plane architecture, horizontal scalability, in-memory processing and other techniques enable enterprises to process billions of rows of data, checked in-line against multiple business rules and policies, ensure that enterprises can confidently implement Acceldata at scale.

Cloud and On-Premises Data

Single platform regardless of data stack location - on-premises, in the cloud or a mix of both. Acceldata architecture presents a single pane of glass for hybrid data and pipelines. (See all integrations)

AI Assisted

Detect anomalies using built in AI algorithms, rapid or cold start by applying basic rules and policies based on data types and usage and many more capabilities to assist enterprise observability initiatives.

Enterprise Class Security

Security is paramount. SOC2 Type 2 certification, audit logs, IP-based access controls, MFA, RBAC, SAML, bug bounty programs and several other security initiatives in place to provide a highly secure offering. Multiple large enterprises have performed the most rigorous security reviews.

Frequently asked questions about Data Observability

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.

Do you have RBAC?

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.

Architected for Modern
Data Teams

Gain intelligence and achieve your outcomes faster

Integrated with all the tools you already use

See all integrations


A cloud-based data warehousing platform that separates storage and compute resources for scalability and flexibility.


A fully scalable relational database management system produced by Teradata Corp, primarily used to manage large data warehousing operations.


Line is an app that powers instant communications on electronic devices such as smartphones, tablet computers and personal computers.

SQL Server

Microsoft's relational database management system, offering a broad set of enterprise data management, business intelligence and analytics applications.

Microsoft Teams

Microsoft Teams is a unified communication and collaboration platform that combines chat, video meetings, file storage, and application integration.


Apache Spark is an open-source, distributed computing system used for big data processing and analytics, offering ease of use and speed.


Slack is a communication and collaboration tool that offers real-time messaging, file sharing, project management, and integrations with various apps for seamless communication and productivity.


A distributed, relational database that delivers high performance, scalability, and concurrent transactions across a unified database.


A cloud computing platform-as-a-service (PaaS) that provides enterprise service management, reporting metrics, self-service, and routing for IT service management, as well as business process automation


A powerful, open-source object-relational database system known for its proven architecture, reliability, and data integrity.


Apache NiFi is an integrated data logistics and simple event processing platform for automating the movement of data between disparate systems.


An incident management platform by Atlassian that ensures critical incidents are never missed, and actions are taken swiftly and effectively.


A digital operations management platform that provides reliable incident notifications via email, push, SMS, and phone, as well as automatic escalations, on-call scheduling, and other functionality to help teams detect and fix infrastructure problems quickly.


A powerful, object-relational database management system (ORDBMS) from Oracle Corporation, known for its scalability, reliability, and wide set of features.


An open-standard and decentralized authentication protocol that allows users to be authenticated by certain co-operating sites (known as Relying Parties) using a third party service.


An identity management platform providing secure identity management with Single Sign-On, Multi-factor Authentication, Lifecycle Management, and more.


Azure Data Lake Storage Gen2, Microsoft's scalable and secure data lake solution that combines the power of a Hadoop compatible file system with integrated hierarchical namespace.

AZURE SQL warehouse

Microsoft's cloud-based, scale-out database service that offers massively parallel processing for data warehousing.


An open-source platform to programmatically author, schedule, and monitor workflows.

Amazon Redshift

Amazon's fully managed, petabyte-scale data warehouse service in the cloud that makes it simple and cost-effective to analyze all your data.

Amazon S3

Amazon Simple Storage Service (S3) is a scalable, high-speed, web-based cloud storage service designed for online backup and archiving of data and applications.


A serverless, interactive query service by Amazon Web Services that makes it easy to analyze data directly in Amazon S3 using standard SQL.


Google's serverless and highly scalable data warehouse designed to make data analysts more productive with unmatched speed for SQL queries.


IBM's family of hybrid data management solutions, designed to provide robust capabilities for transactional and analytic workloads in on-premise, cloud, or hybrid environments.


An AI-driven, open-source platform with collaborative features for big data processing and machine learning.


Electronic mail is a method of exchanging messages ("mail") between people using electronic devices, a critical technology for personal and professional communication.

Google Cloud Storage

Google Cloud Storage is a RESTful online file storage web service for storing and accessing data on Google Cloud Platform infrastructure.


Apache HBase is an open-source, non-relational, distributed database modeled after Google's Bigtable, designed to provide random, real-time read/write access to big data.


Hadoop Distributed File System is a distributed, scalable, and portable file-system written in Java for the Hadoop framework, designed to scale up from single servers to thousands of machines.


Google Hangouts is a communication software that includes messaging, video chat, SMS, and VOIP features.


Apache Hive is a data warehouse software project built on top of Apache Hadoop for providing data query and analysis, primarily providing SQL interface.


An open-source, native analytic database for Apache Hadoop, Impala provides high-performance, low-latency SQL queries on data stored in Hadoop Distributed File System.

Ready to start your
data observability journey?