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DBMS > Apache Druid vs. Hypertable vs. Lovefield vs. TimescaleDB

System Properties Comparison Apache Druid vs. Hypertable vs. Lovefield vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonHypertable  Xexclude from comparisonLovefield  Xexclude from comparisonTimescaleDB  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn open source BigTable implementation based on distributed file systems such as HadoopEmbeddable relational database for web apps written in pure JavaScriptA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMS
Time Series DBMS
Wide column storeRelational DBMSTime Series DBMS
Secondary database modelsRelational 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
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitedruid.apache.orggoogle.github.io/­lovefieldwww.timescale.com
Technical documentationdruid.apache.org/­docs/­latest/­designgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mddocs.timescale.com
DeveloperApache Software Foundation and contributorsHypertable Inc.GoogleTimescale
Initial release2012200920142017
Current release29.0.1, April 20240.9.8.11, March 20162.1.12, February 20172.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoGNU version 3. Commercial license availableOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++JavaScriptC
Server operating systemsLinux
OS X
Unix
Linux
OS X
Windows infoan inofficial Windows port is available
server-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
OS X
Windows
Data schemeyes infoschema-less columns are supportedschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data 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.nonoyes
Secondary indexesyesrestricted infoonly exact value or prefix value scansyesyes
SQL infoSupport of SQLSQL for queryingnoSQL-like query language infovia JavaScript builder patternyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
RESTful HTTP/JSON API
C++ API
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C++
Java
Perl
PHP
Python
Ruby
JavaScript.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnononouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
TriggersnonoUsing read-only observersyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingnoneyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factor on file system levelnoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infousing MemoryDBno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnonofine grained access rights according to SQL-standard

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More resources
Apache DruidHypertableLovefieldTimescaleDB
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