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DBMS > Apache Druid vs. Databricks vs. EXASOL vs. Google Cloud Spanner vs. SQream DB

System Properties Comparison Apache Druid vs. Databricks vs. EXASOL vs. Google Cloud Spanner vs. SQream DB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDatabricks  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSQream DB  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.High-performance, in-memory, MPP database specifically designed for in-memory analytics.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.a GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelRelational DBMS
Time Series DBMS
Document store
Relational DBMS
Relational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Websitedruid.apache.orgwww.databricks.comwww.exasol.comcloud.google.com/­spannersqream.com
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.databricks.comwww.exasol.com/­resourcescloud.google.com/­spanner/­docsdocs.sqream.com
DeveloperApache Software Foundation and contributorsDatabricksExasolGoogleSQream Technologies
Initial release20122013200020172017
Current release29.0.1, April 20242022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, CUDA, Haskell, Java, Scala
Server operating systemsLinux
OS X
Unix
hostedhostedLinux
Data schemeyes infoschema-less columns are supportedFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes, ANSI Standard SQL Types
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.noyesnono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL for queryingwith Databricks SQLyesyes infoQuery statements complying to ANSI 2011yes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
.Net
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Python
R
Scala
Java
Lua
Python
R
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesuser defined functionsnouser defined functions in Python
Triggersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardinghorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesMulti-source replication with 3 replicas for regional instances.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID infoStrict serializable isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)
More information provided by the system vendor
Apache DruidDatabricksEXASOLGoogle Cloud SpannerSQream DB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Apache DruidDatabricksEXASOLGoogle Cloud SpannerSQream DB
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