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DBMS > Datomic vs. Google Cloud Datastore vs. Hawkular Metrics vs. Sphinx vs. STSdb

System Properties Comparison Datomic vs. Google Cloud Datastore vs. Hawkular Metrics vs. Sphinx vs. STSdb

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonSphinx  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Open source search engine for searching in data from different sources, e.g. relational databasesKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelRelational DBMSDocument storeTime Series DBMSSearch engineKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitewww.datomic.comcloud.google.com/­datastorewww.hawkular.orgsphinxsearch.comgithub.com/­STSSoft/­STSdb4
Technical documentationdocs.datomic.comcloud.google.com/­datastore/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidesphinxsearch.com/­docs
DeveloperCognitectGoogleCommunity supported by Red HatSphinx Technologies Inc.STS Soft SC
Initial release20122008201420012011
Current release1.0.6735, June 20233.5.1, February 20234.0.8, September 2015
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoGPLv2, commercial license 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 languageJava, ClojureJavaC++C#
Server operating systemsAll OS with a Java VMhostedLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesnoyes infoprimitive types and user defined types (classes)
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 indexesyesyesnoyes infofull-text index on all search fieldsno
SQL infoSupport of SQLnoSQL-like query language (GQL)noSQL-like query language (SphinxQL)no
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTProprietary protocol.NET Client API
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
Java
Server-side scripts infoStored proceduresyes infoTransaction Functionsusing Google App Enginenonono
TriggersBy using transaction functionsCallbacks using the Google Apps Engineyes infovia Hawkular Alertingnono
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding infobased on CassandraSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication using Paxosselectable replication factor infobased on Cassandranonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownonono
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.Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynoyes 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 Transactionsnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes 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.yes inforecommended only for testing and developmentnono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nonono

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More resources
DatomicGoogle Cloud DatastoreHawkular MetricsSphinxSTSdb
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