Data observability platforms

Updated: January 27, 2024

Data observability platforms are advanced solutions that provide organizations with real-time insights and monitoring capabilities for their data pipelines and workflows. These specialized platforms enable data teams to track the flow of data, detect anomalies, and troubleshoot issues in their data systems with greater efficiency and accuracy. Data observability platforms leverage machine learning algorithms and data visualization tools to identify data quality issues, data drift, and performance bottlenecks, allowing organizations to maintain data integrity and make data-driven decisions confidently. With the ability to monitor data in real-time, data observability platforms enable proactive response to potential issues, ensuring data reliability and availability. By providing end-to-end visibility into data processes and operations, data observability platforms help organizations optimize data performance, improve data governance, and ensure the smooth and reliable functioning of their data infrastructure.

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2024. Observability platform Better Stack secures $10M cash infusion



Better Stack, an observability platform that they launched in 2021 to combine monitoring, logging, and incident management into a single dashboard, has raised $10M. With support for monitoring apps, websites, servers, databases and more, Better Stack delivers alerts, helps schedule things like on-call duties and taps algorithms to normalize metrics from different logs and sources. Better Stack doesn’t stand alone in the market for observability suites. Among its rivals is Observe, which offers tools for storing, managing and analyzing machine-generated data and logs. There’s also Chronosphere (valued at over $1.6 billion), Pantomath and Honeycomb, the last of which secured a $50 million investment last April.


2023. Observability startup Pantomath lands $14M to automate data pipelines



Pantomath, a platform specializing in data observability and traceability, announced a successful $14 million Series A funding round. Pantomath offers organizations a means to detect data quality problems through alerts, troubleshoot using logs and autonomous impact analyses, and pinpoint the root causes of issues for resolution. Although this may seem similar to other data observability platforms in the market, such as Observe (which recently secured $50 million in debt financing), Y Combinator-backed Metaplane, Acceldata, and Manta (which obtained $35 million last year for workforce expansion and tool development), Saxena asserts that Pantomath stands out. According to Saxena, unlike other solutions that primarily focus on data quality by monitoring factors like data volume and freshness within datasets, Pantomath offers a unique approach.


2023. Data observability startup Acceldata raises $10M more



Data observability tools, which empower companies to comprehend, diagnose, and manage the health of data across various IT tools during its lifecycle, remain a prominent trend in the realm of big data technology. In a remarkable instance last year, venture capitalists invested hundreds of millions of dollars within a week in three vendors—Cribl, Monte Carlo, and Coralogix—focused on developing tools for data observability. Acceldata, a startup in the data observability domain, successfully secured $10 million in funding. Acceldata's platform is designed to simplify the entry into this field by monitoring data pipelines and infrastructure, aiding in the investigation and resolution of emerging data quality issues. While this aligns with the standard functionality of data observability tools, Acceldata stands out due to its unique feature: it is among the few products available that monitors an organization's complete data supply chain, encompassing data sources, data enrichment, data consumption, and associated costs.


2023. Observability platform Observe raises $50M in debt, launches gen AI features



Observe, which develops software-as-a-service observability tools for storing, managing and analyzing machine-generated data and logs, has raised $50 million. Observe stores all raw observability data in a data lake, a centralized repository. It curates and layers analytics on top of this data through a “data graph,” ostensibly making it easier for users to navigate and understand the data. Observe competes with app monitoring software; monitoring and log analytics tools like New Relic, Splunk, Datadog and Sumo Logic; and new entrants to the observability space such as Grafana, Chronosphere and Honeycomb. But it’s launching new tools and capabilities to stay ahead of the curve.


2023. Senser launches its AI-enhanced observability platform, raises $9.5M



Senser, a startup that describes itself as an AIOps platform that uses machine learning to help developers and ops teams more easily get to the root causes of outages and service degradations, has raised $9.5 million seed round. At its core, Senser uses the increasingly popular eBPF technology to monitor a company’s infrastructure. The advantage of eBPF is that it runs inside of the Linux kernel and can hence easily see all of the networking and application traffic without any major additional overhead. Given the advantages of this technology, it’s no surprise that a lot of observability companies are betting on it and while the market is getting increasingly saturated, Senser is betting on AI to give it a competitive edge.


2022. Manta, a data observability startup, raises $35M to grow its workforce



Manta, a data lineage platform, has recently secured $35 million in funding. The platform offers automated scanning of an organization's data sources to create comprehensive maps of data flows. Manta aims to address the complexities of enterprise data environments and assist users in preventing significant data incidents. The current iteration of the Manta platform utilizes AI technology to trace the origins of data, including databases, reporting tools, analysis software, and modeling tools, and tracks its journey through various pipelines to applications and services. Additionally, the platform features a "time slicing" capability that enables users to view historical data snapshots and observe changes in data lineage over time. Furthermore, Manta provides an impact analysis tool to assess how planned changes may impact different aspects of the data environment.