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DBMS > Apache Impala vs. Dragonfly vs. Google Cloud Spanner vs. Linter

System Properties Comparison Apache Impala vs. Dragonfly vs. Google Cloud Spanner vs. Linter

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDragonfly  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonLinter  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.RDBMS for high security requirements
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.49
Rank#261  Overall
#38  Key-value stores
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.12
Rank#350  Overall
#152  Relational DBMS
Websiteimpala.apache.orggithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
cloud.google.com/­spannerlinter.ru
Technical documentationimpala.apache.org/­impala-docs.htmlwww.dragonflydb.io/­docscloud.google.com/­spanner/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDragonflyDB team and community contributorsGooglerelex.ru
Initial release2013202320171990
Current release4.1.0, June 20221.0, March 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoBSL 1.1commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C and C++
Server operating systemsLinuxLinuxhostedAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeyesscheme-freeyesyes
Typing infopredefined data types such as float or dateyesstrings, hashes, lists, sets, sorted sets, bit arraysyesyes
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.nononono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infoQuery statements complying to ANSI 2011yes
APIs and other access methodsJDBC
ODBC
Proprietary protocol infoRESP - REdis Serialization ProtocolgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceLuanoyes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersnopublish/subscribe channels provide some trigger functionalitynoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationMulti-source replication with 3 replicas for regional instances.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of command blocks and scriptsACID infoStrict serializable isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPassword-based authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Apache ImpalaDragonflyGoogle Cloud SpannerLinter
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