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DBMS > Apache Druid vs. HarperDB vs. Manticore Search vs. Spark SQL vs. SwayDB

System Properties Comparison Apache Druid vs. HarperDB vs. Manticore Search vs. Spark SQL vs. SwayDB

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHarperDB  Xexclude from comparisonManticore Search  Xexclude from comparisonSpark SQL  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataUltra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Multi-storage database for search, including full-text search.Spark SQL is a component on top of 'Spark Core' for structured data processingAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelRelational DBMS
Time Series DBMS
Document storeSearch engineRelational DBMSKey-value store
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
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
Score0.60
Rank#244  Overall
#38  Document stores
Score0.29
Rank#302  Overall
#21  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Websitedruid.apache.orgwww.harperdb.iomanticoresearch.comspark.apache.org/­sqlswaydb.simer.au
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.harperdb.io/­docsmanual.manticoresearch.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation and contributorsHarperDBManticore SoftwareApache Software FoundationSimer Plaha
Initial release20122017201720142018
Current release29.0.1, April 20243.1, August 20216.0, February 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree community edition availableOpen Source infoGPL version 2Open Source infoApache 2.0Open Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsC++ScalaScala
Server operating systemsLinux
OS X
Unix
Linux
OS X
FreeBSD
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supporteddynamic schemaFixed schemayesschema-free
Typing infopredefined data types such as float or dateyesyes infoJSON data typesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyesno
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.nonoCan index from XMLnono
Secondary indexesyesyesyes infofull-text index on all search fieldsnono
SQL infoSupport of SQLSQL for queryingSQL-like data manipulation statementsSQL-like query languageSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
JDBC
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Java
Python
R
Scala
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1user defined functionsnono
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedA table resides as a whole on one (or more) nodes in a clusterSharding infoPartitioning is done manually, search queries against distributed index is supportedyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes infothe nodes on which a table resides can be definedSynchronous replication based on Galera librarynonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsyes infoisolated transactions for atomic changes and binary logging for safe writesnoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByes infoThe original contents of fields are not stored in the Manticore index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users and rolesnonono

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More resources
Apache DruidHarperDBManticore SearchSpark SQLSwayDB
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