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DBMS > Databricks vs. Ehcache vs. SingleStore

System Properties Comparison Databricks vs. Ehcache vs. SingleStore

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEhcache  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A widely adopted Java cache with tiered storage optionsMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelDocument store
Relational DBMS
Key-value storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score4.79
Rank#66  Overall
#8  Key-value stores
Score4.02
Rank#74  Overall
#39  Relational DBMS
Websitewww.databricks.comwww.ehcache.orgwww.singlestore.com
Technical documentationdocs.databricks.comwww.ehcache.org/­documentationdocs.singlestore.com
DeveloperDatabricksTerracotta Inc, owned by Software AGSingleStore Inc.
Initial release201320092013
Current release3.10.0, March 20228.5, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Go
Server operating systemshostedAll OS with a Java VMLinux info64 bit version required
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesyes
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.yesnono
Secondary indexesyesnoyes
SQL infoSupport of SQLwith Databricks SQLnoyes infobut no triggers and foreign keys
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCacheCluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesPython
R
Scala
JavaBash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes
Triggersyes infoCache Event Listenersno
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby using Terracotta ServerSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infosupports JTA and can work as an XA resourceACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlnoFine grained access control via users, groups and roles
More information provided by the system vendor
DatabricksEhcacheSingleStore infoformer name was MemSQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEhcacheSingleStore infoformer name was MemSQL
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Recent citations in the news

Saudi Arabia’s Sovereign Wealth Fund’s Big AI Bets Include Mistral And Databricks
24 September 2024, Forbes

Databricks could launch IPO in two months but biding time despite investor pressure, CEO says
13 September 2024, ION Analytics

Databricks reportedly paid $2 billion in Tabular acquisition
14 August 2024, TechCrunch

Inside the Snowflake — Databricks Rivalry, and Why Both Fear Microsoft
14 August 2024, Bloomberg

The People in Charge at Databricks as It Moves Toward a Potential IPO
24 July 2024, The Information

provided by Google News

Jira Data Center user? Here's a critical Ehcache vulnerability to spoil your day
22 July 2021, The Register

Atlassian asks customers to patch critical Jira vulnerability
22 July 2021, BleepingComputer

Critical Jira Flaw in Atlassian Could Lead to RCE
22 July 2021, Threatpost

How to partition Sonatype Nexus Repository: Targets, privileges, and roles
9 February 2010, Sonatype Blog

Implementing fallback with cached data
8 October 2018, O'Reilly Media

provided by Google News

SingleStore Partners With Snowflake to Help Users Build Faster, More Efficient Real Time AI Applications
19 September 2024, Business Wire

Third time was the charm for SingleStore in the cloud, CEO says
8 July 2024, The Register

SingleStore CEO sees little future for purpose-built vector databases
24 January 2024, VentureBeat

Achieve near real-time analytics on Amazon DynamoDB with SingleStore
16 September 2024, AWS Blog

Building a Modern Database: Nikita Shamgunov on Postgres and Beyond
18 April 2024, Madrona Venture Group

provided by Google News



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