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DBMS > Apache Impala vs. Databricks vs. Drizzle vs. HarperDB vs. Sequoiadb

System Properties Comparison Apache Impala vs. Databricks vs. Drizzle vs. HarperDB vs. Sequoiadb

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonHarperDB  Xexclude from comparisonSequoiadb  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Ultra-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.NewSQL database with distributed OLTP and SQL
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMSDocument storeDocument store
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.55
Rank#248  Overall
#38  Document stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websiteimpala.apache.orgwww.databricks.comwww.harperdb.iowww.sequoiadb.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comdocs.harperdb.io/­docswww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksDrizzle project, originally started by Brian AkerHarperDBSequoiadb Ltd.
Initial release20132013200820172013
Current release4.1.0, June 20227.2.4, September 20123.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoGNU GPLcommercial infofree community edition availableOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Node.jsC++
Server operating systemsLinuxhostedFreeBSD
Linux
OS X
Linux
OS X
Linux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesdynamic schemaschema-free
Typing infopredefined data types such as float or dateyesyesyes infoJSON data typesyes infooid, date, timestamp, binary, regex
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.noyesnono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLyes infowith proprietary extensionsSQL-like data manipulation statementsSQL-like query language
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
JDBCJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
proprietary protocol using JSON
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
C
C++
Java
PHP
.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
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesnoCustom Functions infosince release 3.1JavaScript
Triggersnono infohooks for callbacks inside the server can be used.nono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication
Source-replica replication
yes infothe nodes on which a table resides can be definedSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDAtomic execution of specific operationsDocument is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and rolessimple password-based access control
More information provided by the system vendor
Apache ImpalaDatabricksDrizzleHarperDBSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache ImpalaDatabricksDrizzleHarperDBSequoiadb
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