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DBMS > Ehcache vs. Google Cloud Bigtable vs. MarkLogic vs. Microsoft Azure Synapse Analytics vs. Sphinx

System Properties Comparison Ehcache vs. Google Cloud Bigtable vs. MarkLogic vs. Microsoft Azure Synapse Analytics vs. Sphinx

Editorial information provided by DB-Engines
NameEhcache  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA widely adopted Java cache with tiered storage optionsGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Operational and transactional Enterprise NoSQL databaseElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value storeKey-value store
Wide column store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.64
Rank#68  Overall
#8  Key-value stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.ehcache.orgcloud.google.com/­bigtablewww.progress.com/­marklogicazure.microsoft.com/­services/­synapse-analyticssphinxsearch.com
Technical documentationwww.ehcache.org/­documentationcloud.google.com/­bigtable/­docswww.progress.com/­marklogic/­documentationdocs.microsoft.com/­azure/­synapse-analyticssphinxsearch.com/­docs
DeveloperTerracotta Inc, owned by Software AGGoogleMarkLogic Corp.MicrosoftSphinx Technologies Inc.
Initial release20092015200120162001
Current release3.10.0, March 202211.0, December 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial inforestricted free version is availablecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++C++
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-free infoSchema can be enforcedyesyes
Typing infopredefined data types such as float or dateyesnoyesyesno
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.nonoyesno
Secondary indexesnonoyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnonoyes infoSQL92yesSQL-like query language (SphinxQL)
APIs and other access methodsJCachegRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
ADO.NET
JDBC
ODBC
Proprietary protocol
Supported programming languagesJavaC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
Java
PHP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonoyes infovia XQuery or JavaScriptTransact SQLno
Triggersyes infoCache Event Listenersnoyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingShardingSharding, horizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby using Terracotta ServerInternal replication in Colossus, and regional replication between two clusters in different zonesyesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable Consistency (Strong, Eventual, Weak)Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infosupports JTA and can work as an XA resourceAtomic single-row operationsACID infocan act as a resource manager in an XA/JTA transactionACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing a tiered cache-storage approachyesyesyesyes 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.yesnoyes, with Range Indexes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control at the document and subdocument levelsyesno

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More resources
EhcacheGoogle Cloud BigtableMarkLogicMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSphinx
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