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DBMS > Datomic vs. Google Cloud Bigtable vs. Sphinx vs. Teradata

System Properties Comparison Datomic vs. Google Cloud Bigtable vs. Sphinx vs. Teradata

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSphinx  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Open source search engine for searching in data from different sources, e.g. relational databasesA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSKey-value store
Wide column store
Search engineRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score5.95
Rank#55  Overall
#5  Search engines
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitewww.datomic.comcloud.google.com/­bigtablesphinxsearch.comwww.teradata.com
Technical documentationdocs.datomic.comcloud.google.com/­bigtable/­docssphinxsearch.com/­docsdocs.teradata.com
DeveloperCognitectGoogleSphinx Technologies Inc.Teradata
Initial release2012201520011984
Current release1.0.7075, December 20233.5.1, February 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++
Server operating systemsAll OS with a Java VMhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
hosted
Linux
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnonoyes
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
Secondary indexesyesnoyes infofull-text index on all search fieldsyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnonoSQL-like query language (SphinxQL)yes infoSQL 2016 + extensions
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Proprietary protocol.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresyes infoTransaction Functionsnonoyes infoUDFs, stored procedures, table functions in parallel
TriggersBy using transaction functionsnonoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersInternal replication in Colossus, and regional replication between two clusters in different zonesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes 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 developmentnoyes
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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DatomicGoogle Cloud BigtableSphinxTeradata
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