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DBMS > Apache Impala vs. Google Cloud Spanner vs. HyperSQL vs. KeyDB

System Properties Comparison Apache Impala vs. Google Cloud Spanner vs. HyperSQL vs. KeyDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  Xexclude from comparisonKeyDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA 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.Multithreaded, transactional RDBMS written in Java infoalso known as HSQLDBAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score3.23
Rank#93  Overall
#48  Relational DBMS
Score0.70
Rank#229  Overall
#32  Key-value stores
Websiteimpala.apache.orgcloud.google.com/­spannerhsqldb.orggithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­spanner/­docshsqldb.org/­web/­hsqlDocsFrame.htmldocs.keydb.dev
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleEQ Alpha Technology Ltd.
Initial release2013201720012019
Current release4.1.0, June 20222.7.2, June 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infobased on BSD licenseOpen Source infoBSD-3
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++
Server operating systemsLinuxhostedAll OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modesLinux
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
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 indexesyesyesyesyes infoby using the Redis Search module
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoQuery statements complying to ANSI 2011yesno
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP API infoJDBC via HTTP
JDBC
ODBC
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC
Java
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoJava, SQLLua
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication with 3 replicas for regional instances.noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoStrict serializable isolationACIDOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardsimple password-based access control and ACL

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More resources
Apache ImpalaGoogle Cloud SpannerHyperSQL infoalso known as HSQLDBKeyDB
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