Venice vs Zato

Overview

Zato

Stacks12

Followers24

Votes0

GitHub Stars988

Forks246

Venice

Stacks0

Followers4

Votes0

GitHub Stars571

Forks106

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Detailed Comparison

Zato	Venice
Connect, integrate and automate all of your systems, APIs and apps, including cloud and legacy ones, using an open-source integration platform in Python. ESB, SOA, REST, API and Cloud Integrations in Python.	It is a derived data storage platform for planet-scale workloads. It is a high-throughput, low-latency, highly-available, horizontally-scalable, eventually-consistent storage system with first-class support for ingesting the output of batch and stream processing jobs.
Integrate everything. In Python.; Connect, integrate and automate all of your systems, APIs and apps, including cloud and legacy ones, using an open-source integration platform in Python.;Say goodbye to integration challenges and hello to peace of mind.	High throughput asynchronous ingestion from batch and streaming sources (e.g. Hadoop and Samza); Low latency online reads via remote queries or in-process caching; Active-active replication between regions with CRDT-based conflict resolution; Multi-cluster support within each region with operator-driven cluster assignment; Multi-tenancy, horizontal scalability and elasticity within each cluster
Statistics
GitHub Stars 988	GitHub Stars 571
GitHub Forks 246	GitHub Forks 106
Stacks 12	Stacks 0
Followers 24	Followers 4
Votes 0	Votes 0
Integrations
Docker MySQL Linux MSSQL Microsoft Azure Amazon S3 PostgreSQL Odoo Ubuntu SQL	Hadoop Samza

What are some alternatives to Zato, Venice?

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

Distributed SQL Query Engine for Big Data

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 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

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 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™ 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

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

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.