We have data on 15 companies that use Apache Pinot. The companies using Apache Pinot are most often found in United States and in the Computer Software industry. Apache Pinot is most often used by companies with >10000 employees and >1000M dollars in revenue. Our data for Apache Pinot usage goes back as far as 1 years.
|Company||Uber Technologies, Inc.|
|DoorDash, Inc.||doordash.com||United States||100M-200M||500-1000|
|Uber Technologies, Inc.||uber.com||United States||>1000M||>10000|
|Prezi Inc.||prezi.com||United States||50M-100M||200-500|
|Stripe, Inc.||stripe.com||United States||200M-1000M||1000-5000|
We use the best indexing techniques combined with advanced data science to monitor the market share of over 15,000 technology products, including Online Analytical Processing (OLAP). By scanning billions of public documents, we are able to collect deep insights on every company, with over 100 data fields per company at an average. In the Online Analytical Processing (OLAP) category, Apache Pinot has a market share of about 0.1%. Other major and competing products in this category include:
Apache Pinot is a realtime distributed OLAP (Online Analytical Processing) datastore that is designed to answer OLAP queries with low latency. It can ingest from batch data sources (such as Hadoop HDFS, Amazon S3, Azure ADLS, Google Cloud Storage) as well as stream data sources (such as Apache Kafka). Its features include pluggable indexing, near realtime ingestion with Apache Kafka supports StringSerializer or Avro formats, SQL-like Query Interface (PQL), horizontally scalable, fault tolerant and more.
Looking at Apache Pinot customers by industry, we find that Computer Software (48%), Internet (8%) and Retail (8%) are the largest segments.
61% of Apache Pinot customers are in United States.
Of all the customers that are using Apache Pinot, 2% are small (<50 employees), 17% are medium-sized and 36% are large (>1000 employees).
Of all the customers that are using Apache Pinot, 8% are small (<$50M), 8% are medium-sized and 42% are large (>$1000M).