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DBMS > EXASOL vs. Google Cloud Datastore vs. Hazelcast vs. Sphinx vs. Splunk

System Properties Comparison EXASOL vs. Google Cloud Datastore vs. Hazelcast vs. Sphinx vs. Splunk

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHazelcast  Xexclude from comparisonSphinx  Xexclude from comparisonSplunk  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA widely adopted in-memory data gridOpen source search engine for searching in data from different sources, e.g. relational databasesAnalytics Platform for Big Data
Primary database modelRelational DBMSDocument storeKey-value storeSearch engineSearch engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Score86.45
Rank#14  Overall
#2  Search engines
Websitewww.exasol.comcloud.google.com/­datastorehazelcast.comsphinxsearch.comwww.splunk.com
Technical documentationwww.exasol.com/­resourcescloud.google.com/­datastore/­docshazelcast.org/­imdg/­docssphinxsearch.com/­docsdocs.splunk.com/­Documentation/­Splunk
DeveloperExasolGoogleHazelcastSphinx Technologies Inc.Splunk Inc.
Initial release20002008200820012003
Current release5.3.6, November 20233.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2, commercial licence availablecommercial infoLimited free edition and free developer edition available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesnoyes
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.nonoyes infothe object must implement a serialization strategyyes
Secondary indexesyesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like query languageSQL-like query language (SphinxQL)no infoSplunk Search Processing Language for search commands
APIs and other access methods.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocolHTTP REST
Supported programming languagesJava
Lua
Python
R
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
Java
JavaScript
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsusing Google App Engineyes infoEvent Listeners, Executor Servicesnoyes
TriggersyesCallbacks using the Google Apps Engineyes infoEventsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infoReplicated MapnoneMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyes infousing Google Cloud Dataflowyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsone or two-phase-commit; repeatable reads; read commitednono infoA 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching
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.yesnoyesno
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlnoAccess rights for users and roles

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More resources
EXASOLGoogle Cloud DatastoreHazelcastSphinxSplunk
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