Apache Phoenix
Apache Phoenix is an analytics platform designed to supplement Hadoop through its powerful OLTP capabilities. It is incredibly fast in its operations so that it can deliver real-time results with low latency values. It is also created to be very integration-friendly, especially with other Apache platforms. Additionally, it is very easy to build from its source code and implement it on the analytics system.
Top Apache Phoenix Alternatives
- TradingView
- Splunk
- Cloudera
- Hadoop HDFS
- Splunk Enterprise
- ObservePoint
- 1010data
- Apache Kudu
- Apache Kylin
- Google Cloud Dataflow
- Apache Ambari
- Snowplow Analytics
- GridGain
- Zendesk Explore
- LeadLander
Top Apache Phoenix Alternatives and Overview
TradingView
TradingView is a platform that allows traders to choose and analyze the stocks before buying them.
Splunk
Splunk is a big data analytics platform used to collect and analyze machine-generated big data and deliver real-time business insights for better decision making.
Hadoop HDFS
Hadoop HDFS is one of the most potent models of Apache Hadoop.
Splunk Enterprise
Splunk Enterprise is a platform that assists the clients in data analysis and management.
ObservePoint
ObserverPoint gives you a rich suite of data validation and testing tools that help you build trust in your data.
1010data
It helps businesses deliver actionable insights quickly based on their enterprise data...
Google Cloud Dataflow
With the help of processing pipelines, it allows the user to monitor, analyse, and integrate...
Apache Ambari
Hadoop is an open-source coding framework that enables the users to analyse and store big...
Snowplow Analytics
They aim to be liberal to inquire whatever queries they want from their data without...
GridGain
It signifies that in practice, GridGain can store and process a user’s data right in...
Zendesk Explore
Along with the measurement feature, it also helps in improving the customer experience...
Apache Phoenix Review and Overview
A good relational database engine massively simplifies the tasks of analyzing loads and loads of data in crucial operations, where time is precious. Apache Phoenix is such a platform compatible with Hadoop. It utilizes extensive parallel data processing as its working methodology, giving it a speed that is uncharacteristic in its competitors at a much lesser resource cost. From singular to bulk operations, everything becomes easier and faster with Apache Phoenix.
A modern relational DB
Apache Phoenix was launched quite recently in 2014, which means not only it had a headstart in the technological department, but it also has a rapidly increasing user and developer base. This developer base has helped it grow exponentially since its release. Each update increases its processing speed and incorporates new technology in it, with the latest update incorporating HBase 2.0 support, allowing extra features and better interoperability. It also has support for OLTP when used with Hadoop, with near-instant response times and transaction speeds. This means that even some of the larger databases can be queried really quickly.
A simple way to install
Apache Phoenix is very easy to implement. It also offers a massive performance boost when compared to its operational costs, which is a sure sign of high return on investments. Apache Phoenix can be easily implemented in the systems of varying capacities, making it quite flexible. Additionally, it can be used in EMR clusters for maximum efficiency. Installation steps are simple and straightforward, and its widespread adoption in the analytics industry means that support documentation by both the users and the dedicated developer is really easy to find. Its extensive support for Apache technologies means that integrations are highly simplified.
A smarter way to query
With the help of an integrated JDBC driver, Apache Phoenix drastically decreases the complexity of querying in a NoSQL environment. Thus, users can get the flexibility associated with NoSQL with none of its practical limitations. Using this driver, users can issue creation, deletion, and modification commands in the SQL table they want to interact with. These interactions can be singular or bulk both.
Company Information
Company Name: The Apache Software Foundation
Founded in: 1999