DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > IBM Db2 Event Store vs. Memcached vs. Spark SQL

System Properties Comparison IBM Db2 Event Store vs. Memcached vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameIBM Db2 Event Store  Xexclude from comparisonMemcached  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDistributed Event Store optimized for Internet of Things use casesIn-memory key-value store, originally intended for cachingSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelEvent Store
Time Series DBMS
Key-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score19.42
Rank#32  Overall
#4  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.ibm.com/­products/­db2-event-storewww.memcached.orgspark.apache.org/­sql
Technical documentationwww.ibm.com/­docs/­en/­db2-event-storegithub.com/­memcached/­memcached/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperIBMDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalApache Software Foundation
Initial release201720032014
Current release2.01.6.25, March 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree developer edition availableOpen Source infoBSD licenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++CScala
Server operating systemsLinux infoLinux, macOS, Windows for the developer additionFreeBSD
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesnonono
SQL infoSupport of SQLyes infothrough the embedded Spark runtimenoSQL-like DML and DDL statements
APIs and other access methodsADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Proprietary protocolJDBC
ODBC
Supported programming languagesC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesActive-active shard replicationnone infoRepcached, a Memcached patch, provides this functionallitynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of dataNo - written data is immutableyesyes
Durability infoSupport for making data persistentYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storagenoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardyes infousing SASL (Simple Authentication and Security Layer) protocolno

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
IBM Db2 Event StoreMemcachedSpark SQL
DB-Engines blog posts

Redis extends the lead in the DB-Engines key-value store ranking
3 February 2014, Matthias Gelbmann

New DB-Engines Ranking shows the popularity of database management systems
3 October 2012, Matthias Gelbmann, Paul Andlinger

show all

Recent citations in the news

Advancements in streaming data storage, real-time analysis and machine learning
25 July 2019, ibm.com

IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere
31 May 2018, Data Center Knowledge

How IBM Is Turning Db2 into an 'AI Database'
3 June 2019, Datanami

Best cloud databases of 2022
4 October 2022, ITPro

Why a robust data management strategy is essential today | IBM HDM
19 September 2019, Express Computer

provided by Google News

Why DDoS Threat Actors Are Shifting Their Tactics
15 March 2024, Infosecurity Magazine

Intel Continues To Demonstrate The Importance Of Software Optimizations: Clear Linux + Xeon Max Benchmarks
23 October 2023, Phoronix

Redis Labs Boldly Joins AWS in Dropping Prices From 10 to 40 Percent
27 March 2024, Yahoo Lifestyle UK

Memcached DDoS: The biggest, baddest denial of service attacker yet
1 March 2018, ZDNet

Why Redis beats Memcached for caching
14 September 2017, InfoWorld

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

1.5 Years of Spark Knowledge in 8 Tips | by Michael Berk
23 December 2023, Towards Data Science

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

provided by Google News



Share this page

Featured Products

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here