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DBMS > Apache Druid vs. Manticore Search vs. QuestDB vs. Sadas Engine

System Properties Comparison Apache Druid vs. Manticore Search vs. QuestDB vs. Sadas Engine

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonManticore Search  Xexclude from comparisonQuestDB  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataMulti-storage database for search, including full-text search.A high performance open source SQL database for time series dataSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelRelational DBMS
Time Series DBMS
Search engineTime Series DBMSRelational DBMS
Secondary database modelsTime Series DBMS infousing the Manticore Columnar LibraryRelational 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
Score0.29
Rank#302  Overall
#21  Search engines
Score2.70
Rank#105  Overall
#8  Time Series DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Websitedruid.apache.orgmanticoresearch.comquestdb.iowww.sadasengine.com
Technical documentationdruid.apache.org/­docs/­latest/­designmanual.manticoresearch.comquestdb.io/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperApache Software Foundation and contributorsManticore SoftwareQuestDB Technology IncSADAS s.r.l.
Initial release2012201720142006
Current release29.0.1, April 20246.0, February 20238.0
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoGPL version 2Open Source infoApache 2.0commercial infofree trial version available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java (Zero-GC), C++, RustC++
Server operating systemsLinux
OS X
Unix
FreeBSD
Linux
macOS
Windows
Linux
macOS
Windows
AIX
Linux
Windows
Data schemeyes infoschema-less columns are supportedFixed schemayes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyesyes
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.noCan index from XMLnono
Secondary indexesyesyes infofull-text index on all search fieldsnoyes
SQL infoSupport of SQLSQL for queryingSQL-like query languageSQL with time-series extensionsyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Proprietary protocol
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresnouser defined functionsnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal partitioning (by timestamps)horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSynchronous replication based on Galera librarySource-replica replication with eventual consistencynone
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 integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes infoisolated transactions for atomic changes and binary logging for safe writesACID for single-table writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes 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.noyes infothrough memory mapped filesyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Apache DruidManticore SearchQuestDBSadas Engine
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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More resources
Apache DruidManticore SearchQuestDBSadas Engine
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