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  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data Tools
  5. Apache Impala vs BDS

Apache Impala vs BDS

OverviewComparisonAlternatives

Overview

Apache Impala
Apache Impala
Stacks145
Followers301
Votes18
GitHub Stars34
Forks33
BDS
BDS
Stacks3
Followers9
Votes0
GitHub Stars996
Forks61

Apache Impala vs BDS: What are the differences?

Developers describe Apache Impala as "Real-time Query for Hadoop". Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time. On the other hand, BDS is detailed as "*Blockchain data parsing and persisting results *". It is a realtime data aggregating, analyzing and visualization service for chain-like unstructured data from all kinds of 3rd party Blockchains.

Apache Impala can be classified as a tool in the "Big Data Tools" category, while BDS is grouped under "Blockchain".

Some of the features offered by Apache Impala are:

  • Do BI-style Queries on Hadoop
  • Unify Your Infrastructure
  • Implement Quickly

On the other hand, BDS provides the following key features:

  • Cover dozens of well-known Blockchain projects, including BTC, ETH, LTC, XRP, BCH, etc
  • Provide an interactive data visualization BI tool
  • Support standard SQL Query statements so that complex query logics can be implemented easily

Apache Impala and BDS are both open source tools. It seems that Apache Impala with 2.2K GitHub stars and 827 forks on GitHub has more adoption than BDS with 324 GitHub stars and 42 GitHub forks.

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Detailed Comparison

Apache Impala
Apache Impala
BDS
BDS

Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.

It is a realtime data aggregating, analyzing and visualization service for chain-like unstructured data from all kinds of 3rd party Blockchains.

Do BI-style Queries on Hadoop;Unify Your Infrastructure;Implement Quickly;Count on Enterprise-class Security;Retain Freedom from Lock-in;Expand the Hadoop User-verse
Cover dozens of well-known Blockchain projects, including BTC, ETH, LTC, XRP, BCH, etc;Provide an interactive data visualization BI tool;Support standard SQL Query statements so that complex query logics can be implemented easily;Provide products that query data on the Blockchain in China and it also provides data visualization BI tools
Statistics
GitHub Stars
34
GitHub Stars
996
GitHub Forks
33
GitHub Forks
61
Stacks
145
Stacks
3
Followers
301
Followers
9
Votes
18
Votes
0
Pros & Cons
Pros
  • 11
    Super fast
  • 1
    High Performance
  • 1
    Distributed
  • 1
    Scalability
  • 1
    Replication
No community feedback yet
Integrations
Hadoop
Hadoop
Mode
Mode
Redash
Redash
Apache Kudu
Apache Kudu
Grafana
Grafana
PostgreSQL
PostgreSQL
Kafka
Kafka
Microsoft SQL Server
Microsoft SQL Server
Confluent
Confluent

What are some alternatives to Apache Impala, BDS?

Apache Spark

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.

Presto

Presto

Distributed SQL Query Engine for Big Data

Amazon Athena

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

Apache Flink

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.

lakeFS

lakeFS

It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.

Druid

Druid

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

Apache Kylin

Apache Kylin

Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.

Splunk

Splunk

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

Vertica

Vertica

It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.

Ethereum

Ethereum

A decentralized platform for applications that run exactly as programmed without any chance of fraud, censorship or third-party interference.

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