Kibana provides flexible analytics and visualization platform for Elasticsearch. It understands large volume of data and easily create bar charts, line and scatter plots, histograms, pie charts, and maps. It can provide real-time summary and charting of streaming data. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.

Kibana - Analytics and search dashboard for Elasticsearch

Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a growing number of use cases. As the heart of the Elastic Stack, it centrally stores your data so you can discover the expected and uncover the unexpected. 
 
 Its feature include: 
 <ul>
	<li>Distributed and Highly Available Search Engine.
	<ul>
		<li>Each index is fully sharded with a configurable number of shards.</li>
		<li>Each shard can have one or more replicas.</li>
		<li>Read / Search operations performed on either one of the replica shard.</li>
	</ul></li>
	<li>Multi Tenant with Multi Types.
	<ul>
		<li>Support for more than one index.</li>
		<li>Support for more than one type per index.</li>
		<li>Index level configuration (number of shards, index storage, &#8230;).</li>
	</ul></li>
	<li>Various set of APIs
	<ul>
		<li>HTTP RESTful API</li>
		<li>Native Java API.</li>
		<li>All APIs perform automatic node operation rerouting.</li>
	</ul></li>
	<li>Document oriented
	<ul>
		<li>No need for upfront schema definition.</li>
		<li>Schema can be defined per type for customization of the indexing process.</li>
	</ul></li>
	<li>Reliable, Asynchronous Write Behind for long term persistency.</li>
	<li>(Near) Real Time Search.</li>
	<li>Built on top of Lucene
	<ul>
		<li>Each shard is a fully functional Lucene index</li>
		<li>All the power of Lucene easily exposed through simple configuration / plugins.</li>
	</ul></li>
	<li>Per operation consistency
	<ul>
		<li>Single document level operations are atomic, consistent, isolated and durable.</li>
	</ul></li>
</ul>

Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a growing number of use cases. As the heart of the Elastic Stack, it centrally stores your data so you can discover the expected and uncover the unexpected. 

ElasticSearch - Distributed, RESTful search and analytics engine

Snowplow is an enterprise-strength marketing and product analytics platform. It identifies your users, and tracks the way they engage with your website or application. It stores your users' behavioural data in a scalable "event data warehouse" you control: in Amazon S3 and (optionally) Amazon Redshift or Postgres. Lets you leverage the biggest range of tools to analyze that data, including big data tools (e.g. Spark) via EMR or more traditional tools e.g. Looker, Mode, Superset, Re:dash to analyze that behavioural data.

Snowplow - Cloud-native web, mobile and event analytics, running on AWS and on-premise with Kafka

Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, dynamic clustering, database integration, and rich document (e.g., Word, PDF) handling. Solr is highly scalable, providing distributed search and index replication, and it powers the search and navigation features of many of the world's largest internet sites. Solr is written in Java and runs as a standalone full-text search server within a servlet container such as Tomcat. Solr uses the Lucene Java search library at its core for full-text indexing and search, and has REST-like HTTP/XML and JSON APIs that make it easy to use from virtually any programming language. Solr's powerful external configuration allows it to be tailored to almost any type of application without Java coding, and it has an extensive plugin architecture when more advanced customization is required. Its feature set include Rich Document Parsing and Indexing (PDF, Word, HTML, etc) using Apache Tika, An Administration Interface, Monitorable Logging, Fast Incremental Updates and Index Replication, Highly Scalable Distributed search with sharded index across multiple hosts, HTTP interface with configurable response formats (XML/XSLT, JSON, Python, Ruby, PHP, Velocity) Solrj is embedded solr. It provides Java based API and it takes care of constructing, parsing, sending and receiving HTTP request.

Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, dynamic clustering, database integration, and rich document (e.g., Word, PDF) handling. Solr is highly scalable, providing distributed search and index replication, and it powers the search and navigation features of many of the world's largest internet sites. 

Solr - Blazing-fast, open source enterprise search platform

The default JavaScript tracking snippet for Google Analytics runs when a web page is first loaded and sends a pageview hit to Google Analytics. If you want to know about more than just pageviews (e.g. where the user clicked, how far they scroll, did they see certain elements, etc.), you have to write code to capture that information yourself.Since most website owners care about a lot of the same types of user interactions, web developers end up writing the same code over and over again for every new site they build.

Autotrack - Automatic and enhanced Google Analytics tracking for common user interactions on the web

TimescaleDB is an open-source database designed to make SQL scalable for time-series data. It is engineered up from PostgreSQL, providing automatic partitioning across time and space (partitioning key), as well as full SQL support. TimescaleDB is packaged as a PostgreSQL extension and released under the Apache 2 open-source license. 
 
TimescaleDB automatically scales and spreads data written to a hypertable into many dynamically-created chunks. Hypertables present the abstraction of a single table, yet transparently partitioned by time and space, they enable high insert rates even at billions of rows.

 TimescaleDB is an open-source database designed to make SQL scalable for time-series data. It is engineered up from PostgreSQL, providing automatic partitioning across time and space (partitioning key), as well as full SQL support. TimescaleDB is packaged as a PostgreSQL extension and released under the Apache 2 open-source license. 

Timescaledb - An open-source time-series database optimized for fast ingest and complex queries

MapD Core is an in-memory, column store, SQL relational database that was designed from the ground up to run on GPUs. MapD Core is the foundational element of a larger data exploration platform that emphasizes speed at scale. By taking advantage of the parallel processing power of the hardware, MapD Core can query billions of rows in milliseconds. Furthermore, by using the graphics pipelines of GPUs, MapD Core can render graphics directly from the server.
 
MapD can operate as a standalone database using the command line or its administration console. MapD can also output to its native interface, MapD Immerse, or to third-party software such as Tableau, Qlik, or Birst, using a variety of connectors. 
 
Within a single server, MapD Core can handle datasets 1.5-3TB in raw size in GPU RAM, or 10-15TB in CPU RAM. In distributed deployments, that number scales linearly.

 MapD Core is an in-memory, column store, SQL relational database that was designed from the ground up to run on GPUs. MapD Core is the foundational element of a larger data exploration platform that emphasizes speed at scale. By taking advantage of the parallel processing power of the hardware, MapD Core can query billions of rows in milliseconds. Furthermore, by using the graphics pipelines of GPUs, MapD Core can render graphics directly from the server.

MapD - The MapD Core database

ClickHouse is an open source column-oriented database management system capable of real time generation of analytical data reports using SQL queries. It is Linearly Scalable, Blazing Fast, Highly Reliable, Fault Tolerant, Data compression, Real time query processing, Web analytics, Vectorized query execution, Local and distributed joins. It can process hundreds of millions to more than a billion rows and tens of gigabytes of data per single server per second.

ClickHouse - Columnar DBMS and Real Time Analytics

Cortex provides horizontally scalable, highly available, multi-tenant, long term storage for Prometheus. Cortex can run across multiple machines in a cluster, exceeding the throughput and storage of a single machine. This enables you to send the metrics from multiple Prometheus servers to a single Cortex cluster and run "globally aggregated" queries across all data in a single place. Cortex makes your PromQL queries blazin' fast through aggressive parallelization and caching.
 
When run in a cluster, Cortex can replicate data between machines. This allows you to survive machine failure without gaps in your graphs. Cortex can isolate data and queries from multiple different independent Prometheus sources in a single cluster, allowing untrusted parties to share the same cluster.
 
Cortex supports Amazon DynamoDB, Google Bigtable, Cassandra, S3, GCS and Microsoft Azure for long term storage of metric data. This allows you to durably store data for longer than the lifetime of any single machine, and use this data for long term capacity planning.

Cortex provides horizontally scalable, highly available, multi-tenant, long term storage for Prometheus. Cortex can run across multiple machines in a cluster, exceeding the throughput and storage of a single machine. This enables you to send the metrics from multiple Prometheus servers to a single Cortex cluster and run "globally aggregated" queries across all data in a single place. Cortex makes your PromQL queries blazin' fast through aggressive parallelization and caching.



Cortex - A multitenant, horizontally scalable Prometheus as a Service

ClickHouse is a fast open-source OLAP database management system. It is column-oriented and allows to generate analytical reports using SQL queries in real-time. Large queries are parallelized using multiple cores, taking all the necessary resources available on the current server. It supports distributed processing, data can reside on different shards. Each shard can be a group of replicas used for fault tolerance. All shards are used to run a query in parallel, transparently for the user.
 
ClickHouse implements user account management using SQL queries and allows for role-based access control configuration similar to what can be found in ANSI SQL standard and popular relational database management systems. It uses asynchronous multi-master replication. After being written to any available replica, all the remaining replicas retrieve their copy in the background. It adaptively chooses how to JOIN multiple tables, by preferring hash-join algorithm and falling back to the merge-join algorithm if there’s more than one large table.

ClickHouse is a fast open-source OLAP database management system. It is column-oriented and allows to generate analytical reports using SQL queries in real-time. Large queries are parallelized using multiple cores, taking all the necessary resources available on the current server. It supports distributed processing, data can reside on different shards. Each shard can be a group of replicas used for fault tolerance. All shards are used to run a query in parallel, transparently for the user.

ClickHouse - Column-oriented database management system that allows generating analytical data reports in real time

QuestDB is a high-performance, open-source SQL database for applications in financial services, IoT, machine learning, DevOps and observability. It includes endpoints for PostgreSQL wire protocol, high-throughput schema-agnostic ingestion using InfluxDB Line Protocol, and a REST API for queries, bulk imports, and exports.
 
QuestDB implements ANSI SQL with native extensions for time-oriented language features. These extensions make it simple to correlate data from multiple sources using relational and time series joins. QuestDB achieves high performance from a column-oriented storage model, massively-parallelized vector execution, SIMD instructions, and various low-latency techniques. The entire codebase was built from the ground up in Java and C++, with no dependencies, and is 100% free from garbage collection.

QuestDB is a high-performance, open-source SQL database for applications in financial services, IoT, machine learning, DevOps and observability. It includes endpoints for PostgreSQL wire protocol, high-throughput schema-agnostic ingestion using InfluxDB Line Protocol, and a REST API for queries, bulk imports, and exports.

QuestDB - Fast relational time-series database

OpenSearch is a community-driven, open source search and analytics suite derived from Apache 2.0 licensed Elasticsearch 7.10.2 & Kibana 7.10.2. It consists of a search engine daemon, OpenSearch, and a visualization and user interface, OpenSearch Dashboards. OpenSearch enables people to easily ingest, secure, search, aggregate, view, and analyze data. These capabilities are popular for use cases such as application search, log analytics, and more.
 
Its features include: 
<ul><li>Log analytics</li><li> Real-time application monitoring</li><li> Clickstream analytics</li><li>Use SQL or a piped processing language to query your data</li><li>Automate index operations</li><li>Monitor and optimize your cluster</li><li>Run search requests in the background</li><li>KNN- Find “nearest neighbors” in your vector data</li><li>Authentication and access control for your cluster</li><li>Anomaly Detection</li></ul>

OpenSearch is a community-driven, open source search and analytics suite derived from Apache 2.0 licensed Elasticsearch 7.10.2 & Kibana 7.10.2. It consists of a search engine daemon, OpenSearch, and a visualization and user interface, OpenSearch Dashboards. OpenSearch enables people to easily ingest, secure, search, aggregate, view, and analyze data. These capabilities are popular for use cases such as application search, log analytics, and more.

OpenSearch - Open source distributed and RESTful search engine

Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low latency analytics. It is an ANSI SQL compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset and many others. It helps to natively query data in Hadoop, S3, Cassandra, MySQL, and many others, without the need for complex, slow, and error-prone processes for copying the data. 
 
Access data from multiple systems within a single query. For example, join historic log data stored in an S3 object storage with customer data stored in a MySQL relational database.

Trino is a highly parallel and distributed query engine, that is built from the ground up for efficient, low latency analytics. It is an ANSI SQL compliant query engine, that works with BI tools such as R, Tableau, Power BI, Superset and many others. It helps to natively query data in Hadoop, S3, Cassandra, MySQL, and many others, without the need for complex, slow, and error-prone processes for copying the data. 

Trino - A query engine that runs at ludicrous speed

Apache Spark is an open source cluster computing system that aims to make data analytics fast — both fast to run and fast to write. To run programs faster, Spark offers a general execution model that can optimize arbitrary operator graphs, and supports in-memory computing, which lets it query data faster than disk-based engines like Hadoop.

Spark - Fast Cluster Computing

A web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more. 

Zeppelin - Multi-purpose Notebook

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