Wizards FluidTableTM
Real-time Streaming Ingestion

Wizards FluidTableTM
Real-time Streaming Ingestion


Streaming Ingestion

Wizards FluidTable employs lock-free ingestion to allow for simultaneous ingestion and querying of high dimensional, high volume data sets. Explore events immediately after they occur.


OLAP Queries

Wizards FluidTable is used to back Wizards DaaS implementations that need to be up all the time. FluidTable supports rolling updates so your data is still available & queryable during Ad Requests.


Analytic Applications

Wizards FluidTable has numerous features built for multi-tenancy. Power user-facing analytic applications designed to be used by thousands of concurrent users.


Records (DataStore Rows)

Wizards FluidTable deployment can handle trillions of events, petabytes of data, and thousands of queries every second. Wizards FluidTable is extremely cost effective at scale and has numerous features built in for cost reduction. Trade off cost and performance with simple configuration knobs.

Stats Updated at 2017-12-18 13:10:03

60% Complete

two hundred fifty eight million six hundred fifty four thousand six hundred ninety eight records in datastore


High Level Architecture

Wizards FluidTable is partially inspired by existing analytic data stores such as Google's BigQuery/Dremel, Google's PowerDrill, and search infrastructure. Wizards FluidTable indexes all ingested data in a custom column format optimized for aggregations and filters. A Wizards FluidTable cluster is composed of various types of processes (called nodes), each designed to do a small set of things very well.


Wizards FluidTable was designed to:

1. Be an always on service

2. Ingest data in real-time

3. Handle slice-n-dice style ad-hoc queries

Wizards FluidTable is built to allow for real-time ingestion of data. You can ingest data and query it immediately upon ingestion, the latency between how quickly the event is reflected in the data is dominated by how long it takes to deliver the event to Wizards FluidTable.

Wizards FluidTable’s data distribution is segment-based and leverages a highly available "deep" storage such as S3 or HDFS. Scaling up (or down) does not require massive copy actions or downtime; in fact, losing any number of historical nodes does not result in data loss because new historical nodes can always be brought up by reading data from "deep" storage.

Wizards FluidTable segments stores data in a custom column format. Segments are scanned directly as part of queries and each Wizards FluidTable server calculates a set of results that are eventually merged at the Broker level. This means the data that is transferred between servers are queries and results, and all computation is done internally as part of the Wizards FluidTable servers.

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