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DBMS > Apache Impala vs. Google Cloud Datastore vs. Microsoft Azure Synapse Analytics vs. SiriDB vs. Sphinx

System Properties Comparison Apache Impala vs. Google Cloud Datastore vs. Microsoft Azure Synapse Analytics vs. SiriDB vs. Sphinx

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSiriDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen Source Time Series DBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSDocument storeRelational DBMSTime Series DBMSSearch engine
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
Score4.36
Rank#72  Overall
#12  Document stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.07
Rank#378  Overall
#42  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteimpala.apache.orgcloud.google.com/­datastoreazure.microsoft.com/­services/­synapse-analyticssiridb.comsphinxsearch.com
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docsdocs.microsoft.com/­azure/­synapse-analyticsdocs.siridb.comsphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleMicrosoftCesbitSphinx Technologies Inc.
Initial release20132008201620172001
Current release4.1.0, June 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercialOpen Source infoMIT LicenseOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++CC++
Server operating systemsLinuxhostedhostedLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes infoNumeric datano
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 indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (GQL)yesnoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
ODBC
HTTP APIProprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
Java
PHP
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
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-reduceusing Google App EngineTransact SQLnono
TriggersnoCallbacks using the Google Apps Enginenonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioningShardingSharding 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 using Paxosyesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflownonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.nonoyes
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)yessimple rights management via user accountsno

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More resources
Apache ImpalaGoogle Cloud DatastoreMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSiriDBSphinx
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