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DBMS > Google Cloud Spanner vs. Hazelcast vs. Ingres vs. MarkLogic

System Properties Comparison Google Cloud Spanner vs. Hazelcast vs. Ingres vs. MarkLogic

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Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonHazelcast  Xexclude from comparisonIngres  Xexclude from comparisonMarkLogic  Xexclude from comparison
DescriptionA 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.A widely adopted in-memory data gridWell established RDBMSOperational and transactional Enterprise NoSQL database
Primary database modelRelational DBMSKey-value storeRelational DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.69
Rank#101  Overall
#51  Relational DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Score3.63
Rank#79  Overall
#43  Relational DBMS
Score4.15
Rank#70  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#8  Search engines
Websitecloud.google.com/­spannerhazelcast.comwww.actian.com/­databases/­ingreswww.progress.com/­marklogic
Technical documentationcloud.google.com/­spanner/­docshazelcast.org/­imdg/­docsdocs.actian.com/­ingreswww.progress.com/­marklogic/­documentation
DeveloperGoogleHazelcastActian CorporationMarkLogic Corp.
Initial release201720081974 infooriginally developed at University Berkely in early 1970s2001
Current release5.3.6, November 202312.0, July 202411.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC++
Server operating systemshostedAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesschema-free infoSchema can be enforced
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyes infothe object must implement a serialization strategyno infobut tools for importing/exporting data from/to XML-files availableyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011SQL-like query languageyesyes infoSQL92
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
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
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesyesyes infovia XQuery or JavaScript
Triggersnoyes infoEventsyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.yes infoReplicated MapIngres Replicatoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationone or two-phase-commit; repeatable reads; read commitedACIDACID infocan act as a resource manager in an XA/JTA transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes, with Range Indexes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlfine grained access rights according to SQL-standardRole-based access control at the document and subdocument levels

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More resources
Google Cloud SpannerHazelcastIngresMarkLogic
Conferences, events and webinars

Progress MarkLogic World
Washington DC, 23-25 September 2024

Recent citations in the news

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23 July 2024, InfoWorld

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Actian Launches Ingres as a Fully-Managed Cloud Service
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