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DBMS > Apache Impala vs. Drizzle vs. Google Cloud Spanner vs. Sphinx

System Properties Comparison Apache Impala vs. Drizzle vs. Google Cloud Spanner vs. Sphinx

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSphinx  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 HadoopMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A 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.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMSRelational DBMSSearch engine
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
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteimpala.apache.orgcloud.google.com/­spannersphinxsearch.com
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­spanner/­docssphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerGoogleSphinx Technologies Inc.
Initial release2013200820172001
Current release4.1.0, June 20227.2.4, September 20123.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGNU GPLcommercialOpen Source infoGPL version 2, commercial licence available
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++
Server operating systemsLinuxFreeBSD
Linux
OS X
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesno
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.nono
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith proprietary extensionsyes infoQuery statements complying to ANSI 2011SQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
JDBCgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Java
PHP
Go
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonono
Triggersnono infohooks for callbacks inside the server can be used.nono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
Multi-source replication with 3 replicas for regional instances.none
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoStrict serializable isolationno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
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, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Apache ImpalaDrizzleGoogle Cloud SpannerSphinx
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