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  1. Stackups
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  4. Databases
  5. Greenplum Database vs IBM DB2

Greenplum Database vs IBM DB2

OverviewComparisonAlternatives

Overview

IBM DB2
IBM DB2
Stacks245
Followers254
Votes19
Greenplum Database
Greenplum Database
Stacks47
Followers111
Votes0
GitHub Stars6.2K
Forks1.7K

Greenplum Database vs IBM DB2: What are the differences?

# Key Differences Between Greenplum Database and IBM DB2

Greenplum Database and IBM DB2 are two popular relational database management systems, each with its strengths and unique features. Understanding the key differences between the two can help users make informed decisions when choosing a database solution for their specific needs.

1. **Architecture**: Greenplum Database is a massively parallel processing (MPP) database designed for analytics and data warehousing. It is built on PostgreSQL and utilizes parallel processing to achieve high performance for complex queries on large datasets. In contrast, IBM DB2 is a general-purpose database management system that supports both OLTP and OLAP workloads. It is designed to provide efficient storage and retrieval of data for transactional processing.

2. **Scalability**: Greenplum Database is known for its scalability, allowing users to add more hardware resources to increase both storage capacity and processing power. Its MPP architecture enables it to scale horizontally by adding more nodes to the cluster, making it ideal for handling big data workloads. On the other hand, IBM DB2 also supports scalability through sharding and partitioning techniques, but it may require more manual configuration compared to Greenplum's more automated scaling capabilities.

3. **Data Types and Indexes**: Greenplum Database and IBM DB2 support a wide range of data types for storing different kinds of data. However, Greenplum Database is known for its extensive support for advanced data types and indexing options, such as columnar storage and bitmap indexes, which are optimized for analytical queries. IBM DB2 also provides a variety of indexing options, but it may not offer the same level of specialization for analytics as Greenplum.

4. **SQL Compatibility**: Both Greenplum Database and IBM DB2 are SQL-compliant databases that support standard SQL queries. However, Greenplum Database, being based on PostgreSQL, offers a high degree of SQL compatibility with PostgreSQL, making it easier for users familiar with PostgreSQL to transition to Greenplum. IBM DB2, on the other hand, has its own SQL dialect and features that may require users to learn new syntax and concepts.

5. **Vendor Support**: Greenplum Database is an open-source database system that is supported by VMware, while IBM DB2 is a proprietary database managed by IBM. The level of vendor support and availability of resources may differ between the two products. Users should consider factors such as community support, documentation, and technical assistance when choosing between Greenplum Database and IBM DB2.

In Summary, the key differences between Greenplum Database and IBM DB2 lie in their architecture, scalability, support for advanced data types and indexes, SQL compatibility, and vendor support.

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Detailed Comparison

IBM DB2
IBM DB2
Greenplum Database
Greenplum Database

DB2 for Linux, UNIX, and Windows is optimized to deliver industry-leading performance across multiple workloads, while lowering administration, storage, development, and server costs.

It is a massively parallel processing (MPP) database server with an architecture specially designed to manage large-scale analytic data warehouses and business intelligence workloads. It is based on PostgreSQL open-source technology.

-
Core SQL Conformance; MPP Architecture; Innovative Query Optimization; Polymorphic Data Storage; Integrated In-Database Analytics
Statistics
GitHub Stars
-
GitHub Stars
6.2K
GitHub Forks
-
GitHub Forks
1.7K
Stacks
245
Stacks
47
Followers
254
Followers
111
Votes
19
Votes
0
Pros & Cons
Pros
  • 7
    Rock solid and very scalable
  • 5
    BLU Analytics is amazingly fast
  • 2
    Native XML support
  • 2
    Secure by default
  • 2
    Easy
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Node.js
Node.js
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JavaScript
PHP
PHP
Ruby
Ruby
Java
Java
Python
Python
C#
C#
.NET
.NET
C++
C++
Perl
Perl
PostgreSQL
PostgreSQL
Kong
Kong
Slick
Slick
Heroku
Heroku
Apache Hive
Apache Hive
Clever Cloud
Clever Cloud
Couchbase
Couchbase
Sequelize
Sequelize
Sails.js
Sails.js
Metabase
Metabase

What are some alternatives to IBM DB2, Greenplum Database?

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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