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DBMS > Apache Druid vs. Databricks vs. SingleStore

System Properties Comparison Apache Druid vs. Databricks vs. SingleStore

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDatabricks  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataThe 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.MySQL 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 modelRelational DBMS
Time Series DBMS
Document store
Relational DBMS
Relational 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
Score3.05
Rank#84  Overall
#45  Relational DBMS
#7  Time Series DBMS
Score99.29
Rank#12  Overall
#2  Document stores
#8  Relational DBMS
Score3.93
Rank#69  Overall
#37  Relational DBMS
Websitedruid.apache.orgwww.databricks.comwww.singlestore.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.databricks.comdocs.singlestore.com
DeveloperApache Software Foundation and contributorsDatabricksSingleStore Inc.
Initial release201220132013
Current release30.0.0, June 20248.5, January 2024
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, Go
Server operating systemsLinux
OS X
Unix
hostedLinux info64 bit version required
Data schemeyes infoschema-less columns are supportedFlexible Schema (defined schema, partial schema, schema free)yes
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.noyesno
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL for queryingwith Databricks SQLyes infobut no triggers and foreign keys
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Python
R
Scala
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesSource-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 ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes 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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemFine grained access control via users, groups and roles

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More resources
Apache DruidDatabricksSingleStore infoformer name was MemSQL
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Recent citations in the news

How to connect DataGrip to Apache Druid
18 October 2021, Towards Data Science

Apache® Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers’ Choice Awards
26 January 2024, Business Wire

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

Streaming fast: Druid’s event-based database practices for sub-second trillion row response
21 February 2022, Blocks and Files

Apache Druid 25.0 Delivers Multi-Stage Query Engine and Kubernetes Task Management
19 January 2023, infoq.com

provided by Google News

Databricks to boost hiring, invest $250 million in India for AI expansion
24 April 2025, Reuters

Databricks Just Dropped $250M in India--Here's Why It Could Redefine the Global AI Race
24 April 2025, Yahoo Finance

Databricks to Hire Hundreds in India to Accelerate AI Boom
24 April 2025, Bloomberg.com

Databricks to Invest $250 Million in India to Boost AI Talent and R&D
24 April 2025, outlookbusiness.com

BigQuery is 5x bigger than Snowflake and Databricks: What Google is doing to make it even better
17 April 2025, VentureBeat

provided by Google News

SingleStore Appoints Nadeem Asghar as Chief Technology Officer
17 April 2025, citybiz

SingleStore Acquires BryteFlow ​​to Accelerate Adoption of Real-Time Analytics, GenAI
3 October 2024, Business Wire

SingleStore acquires BryteFlow to boost data ingestion capabilities
3 October 2024, InfoWorld

SingleStore's BryteFlow acquisition targets data integration
3 October 2024, TechTarget

Announcing watsonx.ai and SingleStore for generative AI applications
16 October 2024, IBM

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