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DBMS > Bangdb vs. Google Cloud Spanner vs. Sphinx vs. Teradata Aster

System Properties Comparison Bangdb vs. Google Cloud Spanner vs. Sphinx vs. Teradata Aster

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Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSphinx  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionConverged and high performance database for device data, events, time series, document and graphA 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.Open source search engine for searching in data from different sources, e.g. relational databasesPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitebangdb.comcloud.google.com/­spannersphinxsearch.com
Technical documentationdocs.bangdb.comcloud.google.com/­spanner/­docssphinxsearch.com/­docs
DeveloperSachin Sinha, BangDBGoogleSphinx Technologies Inc.Teradata
Initial release2012201720012005
Current releaseBangDB 2.0, October 20213.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoBSD 3commercialOpen 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 languageC, C++C++
Server operating systemsLinuxhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesnoyes
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 infoin Aster File Store
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL like support with command line toolyes infoQuery statements complying to ANSI 2011SQL-like query language (SphinxQL)yes
APIs and other access methodsProprietary protocol
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Proprietary protocolADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Java
Python
Go
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnononoR packages
Triggersyes, Notifications (with Streaming only)nonono
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)Multi-source replication with 3 replicas for regional instances.noneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationnoACID
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyes 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, run db with in-memory only modenono
User concepts infoAccess controlyes (enterprise version only)Access 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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More resources
BangdbGoogle Cloud SpannerSphinxTeradata Aster
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