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DBMS > Google Cloud Bigtable vs. Heroic vs. SingleStore vs. Teradata Aster

System Properties Comparison Google Cloud Bigtable vs. Heroic vs. SingleStore vs. Teradata Aster

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHeroic  Xexclude from comparisonSingleStore infoformer name was MemSQL  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.
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typePlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value store
Wide column store
Time Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score0.13
Rank#335  Overall
#29  Time Series DBMS
Score4.02
Rank#74  Overall
#39  Relational DBMS
Websitecloud.google.com/­bigtablegithub.com/­spotify/­heroicwww.singlestore.com
Technical documentationcloud.google.com/­bigtable/­docsspotify.github.io/­heroicdocs.singlestore.com
DeveloperGoogleSpotifySingleStore Inc.Teradata
Initial release2015201420132005
Current release8.5, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree developer edition availablecommercial
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 languageJavaC++, Go
Server operating systemshostedLinux info64 bit version requiredLinux
Data schemeschema-freeschema-freeyesFlexible 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 datenoyesyesyes
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.nononoyes infoin Aster File Store
Secondary indexesnoyes infovia Elasticsearchyesyes
SQL infoSupport of SQLnonoyes infobut no triggers and foreign keysyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
Bash
C
C#
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnonoyesR packages
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infohash partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyesSource-replica replication infostores two copies of each physical data partition on two separate nodesyes 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 methodsyesnono infocan define user-defined aggregate functions for map-reduce-style calculationsyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Fine grained access control via users, groups and rolesfine grained access rights according to SQL-standard

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More resources
Google Cloud BigtableHeroicSingleStore infoformer name was MemSQLTeradata Aster
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