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DBMS > Apache Druid vs. Spark SQL vs. Transwarp Hippo

System Properties Comparison Apache Druid vs. Spark SQL vs. Transwarp Hippo

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonSpark SQL  Xexclude from comparisonTranswarp Hippo  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataSpark SQL is a component on top of 'Spark Core' for structured data processingCloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.05
Rank#386  Overall
#16  Vector DBMS
Websitedruid.apache.orgspark.apache.org/­sqlwww.transwarp.cn/­en/­subproduct/­hippo
Technical documentationdruid.apache.org/­docs/­latest/­designspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsApache Software Foundation
Initial release201220142023
Current release29.0.1, April 20243.5.0 ( 2.13), September 20231.0, May 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaC++
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows
Linux
macOS
Data schemeyes infoschema-less columns are supportedyes
Typing infopredefined data types such as float or dateyesyesVector, Numeric and String
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.nonono
Secondary indexesyesnono
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Java
Python
R
Scala
C++
Java
Python
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
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 systemnoRole based access control and fine grained access rights

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More resources
Apache DruidSpark SQLTranswarp Hippo
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