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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. StreamSets vs Vertica

StreamSets vs Vertica

OverviewComparisonAlternatives

Overview

Vertica
Vertica
Stacks90
Followers120
Votes16
StreamSets
StreamSets
Stacks53
Followers133
Votes0

Vertica vs StreamSets: What are the differences?

Developers describe Vertica as "Storage platform designed to handle large volumes of data". It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure. On the other hand, StreamSets is detailed as "Where DevOps Meets Data Integration". The industry's first data operations platform for full life-cycle management of data in motion.

Vertica and StreamSets can be primarily classified as "Big Data" tools.

Some of the features offered by Vertica are:

  • Analyze All of Your Data. No longer move data or settle for siloed views
  • Achieve Scale and Performance
  • Fear of growing data volumes and users is a thing of the past

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

  • Build Batch & Streaming Pipelines in Hours
  • Map and Monitor Runtime Performance
  • Protect Sensitive Data as it Arrives

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Detailed Comparison

Vertica
Vertica
StreamSets
StreamSets

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

An end-to-end data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps.

Analyze All of Your Data. No longer move data or settle for siloed views;Achieve Scale and Performance;Fear of growing data volumes and users is a thing of the past;Future-Proof Your Analytics
Only StreamSets provides a single design experience for all design patterns (batch, streaming, CDC, ETL, ELT, and ML pipelines) for 10x greater developer productivity; smart data pipelines that are resilient to change for 80% less breakages; and a single pane of glass for managing and monitoring all pipelines across hybrid and cloud architectures to eliminate blind spots and control gaps.
Statistics
Stacks
90
Stacks
53
Followers
120
Followers
133
Votes
16
Votes
0
Pros & Cons
Pros
  • 3
    Shared nothing or shared everything architecture
  • 1
    Partition pruning and predicate push down on Parquet
  • 1
    Vertica is the only product which offers partition prun
  • 1
    Query-Optimized Storage
  • 1
    Fully automated Database Designer tool
Cons
  • 2
    No user community
  • 1
    Crashes
Integrations
Oracle
Oracle
Golang
Golang
MongoDB
MongoDB
MySQL
MySQL
Sass
Sass
Mode
Mode
PowerBI
PowerBI
Tableau
Tableau
Talend
Talend
HBase
HBase
Databricks
Databricks
Amazon Redshift
Amazon Redshift
MySQL
MySQL
gRPC
gRPC
Google BigQuery
Google BigQuery
Amazon Kinesis
Amazon Kinesis
Cassandra
Cassandra
Hadoop
Hadoop
Redis
Redis

What are some alternatives to Vertica, StreamSets?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Kafka

Kafka

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

RabbitMQ

RabbitMQ

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

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