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DBMS > Apache Druid vs. Apache Impala vs. HarperDB vs. Splice Machine

System Properties Comparison Apache Druid vs. Apache Impala vs. HarperDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Impala  Xexclude from comparisonHarperDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic DBMS for HadoopUltra-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.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSDocument storeRelational DBMS
Secondary database modelsDocument store
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
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.60
Rank#244  Overall
#38  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitedruid.apache.orgimpala.apache.orgwww.harperdb.iosplicemachine.com
Technical documentationdruid.apache.org/­docs/­latest/­designimpala.apache.org/­impala-docs.htmldocs.harperdb.io/­docssplicemachine.com/­how-it-works
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by ClouderaHarperDBSplice Machine
Initial release2012201320172014
Current release29.0.1, April 20244.1.0, June 20223.1, August 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2commercial infofree community edition availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Node.jsJava
Server operating systemsLinux
OS X
Unix
LinuxLinux
OS X
Linux
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesdynamic schemayes
Typing infopredefined data types such as float or dateyesyesyes infoJSON data typesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsSQL-like data manipulation statementsyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBC.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
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceCustom Functions infosince release 3.1yes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingA table resides as a whole on one (or more) nodes in a clusterShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factoryes infothe nodes on which a table resides can be definedMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoAtomic execution of specific operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
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 infobased on Apache Sentry and KerberosAccess rights for users and rolesAccess rights for users, groups and roles according to SQL-standard

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More resources
Apache DruidApache ImpalaHarperDBSplice Machine
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