IBM DB2 vs MemSQL

Overview

MemSQL

Stacks86

Followers184

Votes44

IBM DB2

Stacks245

Followers254

Votes19

IBM DB2 vs MemSQL: What are the differences?

Introduction

Here are the key differences between IBM DB2 and MemSQL:

Architecture: IBM DB2 is a traditional, disk-based relational database management system (RDBMS) that follows the client-server architecture, whereas MemSQL is an in-memory database that combines real-time data processing with an integrated data warehouse for analytics, using a distributed architecture with a shared-nothing design. This enables MemSQL to achieve high performance and scale horizontally.
Data Processing Speed: MemSQL is known for its high-speed data processing capabilities, as it leverages in-memory technology to reduce I/O bottlenecks and optimize query performance. On the other hand, while IBM DB2 has improved its processing speed over time, it may not match the real-time processing capabilities of MemSQL due to its disk-based nature.
Scalability: MemSQL is designed to scale-out horizontally by adding more nodes to the cluster, allowing it to handle large amounts of data and high workloads efficiently. In contrast, IBM DB2 may require more manual effort and tuning to scale horizontally, making it potentially less suited for rapidly growing data volumes and performance demands.
Data Consistency: IBM DB2 ensures strong data consistency by supporting ACID (Atomicity, Consistency, Isolation, Durability) properties, which are essential for transactional workloads. MemSQL, on the other hand, may provide tunable consistency levels that prioritize speed and availability, which can be suitable for certain use cases but may compromise strong consistency.
SQL Compliance and Ecosystem: IBM DB2 is a well-established RDBMS with comprehensive SQL support and a mature ecosystem of tools, integrations, and enterprise features. While MemSQL also supports standard SQL queries, its ecosystem may not be as extensive or mature as IBM DB2's, potentially requiring additional development effort for integration and maintenance.

Summary

In Summary, IBM DB2 is a traditional RDBMS known for its reliability and robust feature set, while MemSQL stands out for its in-memory processing speed, scalability, and real-time analytics capabilities with a distributed architecture tailored for performance and agility.

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Detailed Comparison

MemSQL	IBM DB2
MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.	DB2 for Linux, UNIX, and Windows is optimized to deliver industry-leading performance across multiple workloads, while lowering administration, storage, development, and server costs.
ANSI SQL Support;Fully-distributed Joins;Compiled Queries; ACID Compliance;In-Memory Tables;On-Disk Tables; Massively Parallel Execution;Lock Free Data Structures;JSON Support; High Availability; Online Backup and Restore;Online Replication	-
Statistics
Stacks 86	Stacks 245
Followers 184	Followers 254
Votes 44	Votes 19
Pros & Cons
Pros 9 Distributed 5 Realtime 4 Sql 4 JSON 4 Columnstore	Pros 7 Rock solid and very scalable 5 BLU Analytics is amazingly fast 2 Native XML support 2 Secure by default 2 Easy
Integrations
Google Compute Engine MySQL QlikView	Node.js JavaScript PHP Ruby Java Python C# .NET C++ Perl

What are some alternatives to MemSQL, IBM DB2?

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.

Redis

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

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

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

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 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

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 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.

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