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DBMS > Apache Impala vs. HugeGraph vs. Microsoft Azure AI Search vs. Sphinx vs. Sqrrl

System Properties Comparison Apache Impala vs. HugeGraph vs. Microsoft Azure AI Search vs. Sphinx vs. Sqrrl

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopA fast-speed and highly-scalable Graph DBMSSearch-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databasesAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMSGraph DBMSSearch engineSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument storeVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websiteimpala.apache.orggithub.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­en-us/­services/­searchsphinxsearch.comsqrrl.com
Technical documentationimpala.apache.org/­impala-docs.htmlhugegraph.apache.org/­docslearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBaiduMicrosoftSphinx Technologies Inc.Amazon infooriginally Sqrrl Data, Inc.
Initial release20132018201520012012
Current release4.1.0, June 20220.9V13.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialOpen Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++Java
Server operating systemsLinuxLinux
macOS
Unix
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonono
Secondary indexesyesyes infoalso supports composite index and range indexyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoSQL-like query language (SphinxQL)no
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP API
TinkerPop Gremlin
RESTful HTTP APIProprietary protocolAccumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesAll languages supporting JDBC/ODBCGroovy
Java
Python
C#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceasynchronous Gremlin script jobsnonono
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoImplicit feature of the cloud servicenoneselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducevia hugegraph-sparknonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynoyes infoedges in graphnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
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 KerberosUsers, roles and permissionsyes infousing Azure authenticationnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Apache ImpalaHugeGraphMicrosoft Azure AI SearchSphinxSqrrl
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