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

Sybase vs Vertica

OverviewComparisonAlternatives

Overview

Vertica
Vertica
Stacks88
Followers120
Votes16
Sybase
Sybase
Stacks41
Followers80
Votes10

Sybase vs Vertica: What are the differences?

Sybase vs Vertica: Key Differences

Sybase and Vertica are both popular database management systems used in the industry. While they share some similarities, there are several key differences that set them apart. Here are the six main differences between Sybase and Vertica:

  1. Data Structure: Sybase uses a row-based storage structure, which means that data is stored in rows within tables. On the other hand, Vertica uses a columnar storage structure, where data is stored in columns rather than rows. This columnar storage provides several advantages, including better compression and performance for analytical queries.

  2. Parallel Processing: Vertica excels in parallel processing capabilities, making it an ideal choice for handling large-scale data analytics workloads. It utilizes a shared-nothing architecture, allowing it to distribute data and query processing across multiple nodes in a cluster, which leads to faster query execution. Sybase, on the other hand, does not provide the same level of advanced parallel processing capabilities.

  3. Compression: Vertica offers highly efficient compression mechanisms, enabling it to store and query large volumes of data in a compact manner. Its columnar compression techniques, such as encoding and data compression algorithms, help reduce storage requirements and improve query performance. Sybase also provides compression options, but they may not be as effective as Vertica's specialized compression techniques.

  4. Analytical Capabilities: Vertica is specifically designed for analytics and has built-in features that facilitate complex analytical queries. It supports advanced analytics functions like machine learning, geospatial analysis, and time series analysis. Sybase, on the other hand, is more focused on transaction processing rather than analytics, although it does have some analytical capabilities.

  5. Distributed Database: Vertica is inherently designed to work in a distributed environment. It can efficiently handle distributed data across multiple nodes or servers, making it suitable for big data environments and scalable workloads. Sybase also supports distributed databases, but it may not have the same level of architectural support and scalability as Vertica.

  6. Vendor and Licensing: Sybase is owned by SAP, a well-established enterprise software vendor. It is available under different licensing models, including perpetual licenses and subscription models. Vertica, on the other hand, is owned by Micro Focus, and its licensing model usually involves an annual subscription. The choice between the two may depend on the specific requirements and preferences of the organization or business.

In summary, Sybase and Vertica differ in their data structure, parallel processing capabilities, compression techniques, analytical features, distributed database support, and vendor licensing. Understanding these key differences can help organizations choose the right database management system based on their specific needs and use cases.

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Detailed Comparison

Vertica
Vertica
Sybase
Sybase

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

Modernize and accelerate your transaction-based applications on premise and in the cloud. This high-performance SQL database server uses a relational management model to meet rising demand for performance, reliability, and efficiency in every industry.

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
Faster, more secure transfer of database files; Multiversion concurrency control (MVCC); Three-system monitoring procedures
Statistics
Stacks
88
Stacks
41
Followers
120
Followers
80
Votes
16
Votes
10
Pros & Cons
Pros
  • 3
    Shared nothing or shared everything architecture
  • 1
    Offers users the freedom to choose deployment mode
  • 1
    Flexible architecture suits nearly any project
  • 1
    Reduce costs as reduced hardware is required
  • 1
    Partition pruning and predicate push down on Parquet
Pros
  • 1
    Sybase has at least 200000 from 15 years ago
  • 1
    SAP Replication server este net superior replicarii din
  • 1
    SAP Replication server is clearly superior to MS SQL Se
  • 1
    HADR does not lose data is superior to Allwayson which
  • 1
    Max number of connection is 350000
Integrations
Oracle
Oracle
Golang
Golang
MongoDB
MongoDB
MySQL
MySQL
Sass
Sass
Mode
Mode
PowerBI
PowerBI
Tableau
Tableau
Talend
Talend
No integrations available

What are some alternatives to Vertica, Sybase?

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.

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.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

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