Outperforms data warehouses by 100X
Druid excels over data warehouses for ad-hoc OLAP queries where low latency is a must. Data warehouses are built to answer large, complex SQL queries, where speed is not the primary concern.
High-speed ingestion
Druid works out of the box with stream hubs (Apache Kafka, Kinesis), data lakes (HDFS, S3, Google Cloud Storage, Azure storage), HTTP, local files, and more.Ad-hoc analytics
Druid fully indexes data into a novel storage format that is highly optimized for OLAP analytic queries.Instant results
Druid is built for sub-second SQL queries, even at high concurrency. Druid is great at powering analytics applications.Imply makes Druid enterprise-ready
Visualize data with Imply Pivot
Imply Pivot lets users answer their own questions. Explore, drill down, and share insights through a simple point-and-click interface. Imply Pivot is ideal for ad-hoc analytics.
- Every visualization is fully interactive and supports drill down.
- Updates occur in real-time with new incoming data.
- Alert on custom-defined changes in data.
- Create and share drag-and-drop dashboards.
Manage Druid clusters with Imply Manager
- Deploy, scale and update clusters
- Easily view your cluster status.
- One click, no downtime software updates.
- Designed to work with Kubernetes.
Monitor Druid queries with Imply Clarity
- Track every query that is made in your cluster.
- Pinpoint performance bottlenecks.
- Easily view every critical Druid metric.
Set and get custom data alerts
Configurable alerts let you set triggers and get real-time notification of changes in your Pivot data cubes or dashboards. You can set relative or absolute thresholds on one or more conditions and even preview likely alert incidence from historical data. Then you can get notifications via email, in-product or from third party apps via webhooks integration.
Protect your cluster with Imply Security
- Row, column and table level security
- Role-based access control
- End-to-end data encryption
- Integrate with LDAP, Kerberos, OAuth and more