Apache Pinot
#276in DatabasesWhat is Apache Pinot?
Apache Pinot is a fast, scalable real-time analytics database. It is a column-oriented distributed Online Analytics Processing (OLAP) database designed for high concurrency and low latency. It can scan petabyte-scale data and produce results even as fast as single-digit milliseconds.
Apache Pinot is a tool in the Databases category of a tech stack.
Key Features
Real-time ingestion (Kafka, Kinesis, Pulsar)Real-time upsertsBatch ingestion (Flink, Hadoop, Spark)SQL ingestion (Snowflake,
BigQuery)Ingestion time pre-processing (transforms, flattening, rollups)Flexible indexing types (star-tree, Bloom filter, forward, inverted,
geospatial, JSON, range, text, timestamp)Automatic data replication and partitioningEncryption (on disktransport)Easy table management (backfills, dynamic re-indexing, minions for dynamic data layout changes)Schema evolutionNested columns
Apache Pinot Pros & Cons
Pros of Apache Pinot
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Cons of Apache Pinot
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Apache Pinot Alternatives & Comparisons
What are some alternatives to Apache Pinot?
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
Apache Flink
Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
