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  5. lakeFS vs Apache Spark

lakeFS vs Apache Spark

OverviewComparisonAlternatives

Overview

Apache Spark
Apache Spark
Stacks3.1K
Followers3.5K
Votes140
GitHub Stars42.2K
Forks28.9K
lakeFS
lakeFS
Stacks3
Followers3
Votes37
GitHub Stars5.0K
Forks403

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Detailed Comparison

Apache Spark
Apache Spark
lakeFS
lakeFS

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.

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.

Run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk;Write applications quickly in Java, Scala or Python;Combine SQL, streaming, and complex analytics;Spark runs on Hadoop, Mesos, standalone, or in the cloud. It can access diverse data sources including HDFS, Cassandra, HBase, S3
Zero copy version management; Any data formats: structured, unstructured, open table, etc; Scales to Petabytes and millions of objects with negligible performance impact; Seamless integration with all your data stack
Statistics
GitHub Stars
42.2K
GitHub Stars
5.0K
GitHub Forks
28.9K
GitHub Forks
403
Stacks
3.1K
Stacks
3
Followers
3.5K
Followers
3
Votes
140
Votes
37
Pros & Cons
Pros
  • 61
    Open-source
  • 48
    Fast and Flexible
  • 8
    Great for distributed SQL like applications
  • 8
    One platform for every big data problem
  • 6
    Easy to install and to use
Cons
  • 4
    Speed
Pros
  • 2
    Cloud agnostic
  • 2
    Format agnostic
  • 2
    Easy to use
  • 2
    Cloud agnostics
  • 2
    Strong Team
Integrations
No integrations available
Cloudera Enterprise
Cloudera Enterprise
Python
Python
Kafka
Kafka
Airflow
Airflow
Dremio
Dremio
DuckDB
DuckDB
Apache Hive
Apache Hive
Presto
Presto
Amazon Athena
Amazon Athena
dbt
dbt

What are some alternatives to Apache Spark, lakeFS?

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.

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.

Apache Impala

Apache Impala

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.

Vertica

Vertica

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

Azure Synapse

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

Apache Kudu

Apache Kudu

A new addition to the open source Apache Hadoop ecosystem, Kudu completes Hadoop's storage layer to enable fast analytics on fast data.

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