Apache Hadoop HDFS vs Parseable
Apache Hadoop HDFS
hadoop.apache.org
Parseable
parseable.comSide by side
| Figure | Apache Hadoop HDFS | Parseable |
|---|---|---|
| Price from | Free | $0.39/mo |
| Free plan | Yes | Yes |
| Free trial | — | Yes |
| Open source | Yes | — |
| Web | — | Yes |
| Windows | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 2 | 3 |
| Spec score · Data Lake Software | 8.9 (#1) | 8.1 (#5) |
| Architecture | A cluster uses a NameNode for namespace and access coordination and DataNodes for block storage and serving reads and writes. | The product is written in Rust and uses an object-store-native, open columnar format. |
| Integrations | Hadoop 3.5.0 includes a FileSystem implementation for Google Cloud Storage, and its documentation also lists connectors for Amazon S3, Azure Blob Storage, and Azure Data Lake Storage. | The site lists integrations including Prometheus, Grafana, Kafka, Redpanda, AWS, Azure, OpenTelemetry, Kubernetes, Fluent Bit, Fluentd, Vector, MinIO, OpenAI, and Anthropic. |
| Security | Production clusters are expected to use Kerberos for caller authentication and access control. | The site identifies Parseable as GDPR certified and SOC 2 Type II. |
| Support | The project asks users not to request private support from its non-paid volunteers and directs help requests to module mailing lists. | The Enterprise plan includes premium support with a dedicated SLA, and the site lists 24×7 product support via portal in its plan comparison. |
Plans
Apache Hadoop HDFS
- Apache Hadoop HDFSFree
- Apache Hadoop / HDFS open-source distributionFree
In their own words
Apache Hadoop HDFS
Apache Hadoop HDFS is a free, open-source distributed file system for high-throughput access to large application data sets on commodity hardware. It is designed for clusters of hundreds of nodes and can support tens of millions of files in one instance. HDFS copies file blocks across machines and detects failed DataNodes so it can start creating replacement copies. Its design prioritizes batch processing and streaming throughput rather than low-latency interactive workloads. Files follow a write-once, read-many model: appends and truncates are supported, but arbitrary in-place changes are not. Applications can connect through Java, a C wrapper, REST, a browser interface or an NFS gateway. The documentation lists connectors for Google Cloud Storage, Amazon S3, Azure Blob Storage and Azure Data Lake Storage. HDFS supports transparent encryption. Apache warns that without Kerberos caller authentication, anyone with network access to cluster servers can access data and run code, and recommends securing clusters before production. Apache also recommends checking release downloads with GPG signatures or SHA-512 checksums. The listed stable release is Hadoop 3.5.0, dated April 2, 2026.
Parseable
Parseable is an open observability platform for logs, metrics, and distributed traces. Its features include dashboards, alerts, service maps, error pages, and root-cause analysis. Users can query telemetry with SQL or natural language, and use forecasting and AI analysis. Written in Rust, it uses an open columnar format designed for object storage. Deployment choices include self-hosted open source, managed cloud, and enterprise deployments with bring-your-own-cloud options. Listed integrations include Prometheus, Grafana, Kafka, Redpanda, AWS, Azure, OpenTelemetry, Kubernetes, Fluent Bit, Fluentd, Vector, MinIO, OpenAI, and Anthropic. Its MCP connects AI agents to live telemetry through structured tools, and its Slack bot brings operational answers into Slack. The free OSS plan includes SQL queries, dashboards, threshold alerts, OIDC SSO, unlimited users, and customizable retention and object storage. OSS supports only one query node and lacks groups for RBAC. Cloud costs $0.39 per month, billed per GB ingested, and includes 365 days of retention and a 14-day trial. Enterprise starts at $15,000.00 per year.