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DBMS > Google Cloud Bigtable vs. Kinetica vs. Memcached vs. SingleStore

System Properties Comparison Google Cloud Bigtable vs. Kinetica vs. Memcached vs. SingleStore

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonKinetica  Xexclude from comparisonMemcached  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Fully vectorized database across both GPUs and CPUsIn-memory key-value store, originally intended for cachingMySQL 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 type
Primary database modelKey-value store
Wide column store
Relational DBMSKey-value storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document 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
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score16.84
Rank#32  Overall
#4  Key-value stores
Score4.02
Rank#74  Overall
#39  Relational DBMS
Websitecloud.google.com/­bigtablewww.kinetica.comwww.memcached.orgwww.singlestore.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.kinetica.comgithub.com/­memcached/­memcached/­wikidocs.singlestore.com
DeveloperGoogleKineticaDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalSingleStore Inc.
Initial release2015201220032013
Current release7.1, August 20211.6.29, June 20248.5, January 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD licensecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++CC++, Go
Server operating systemshostedLinuxFreeBSD
Linux
OS X
Unix
Windows
Linux info64 bit version required
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesnoyes
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 indexesnoyesnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoyes infobut no triggers and foreign keys
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
RESTful HTTP API
Proprietary protocolCluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functionsnoyes
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationnone infoRepcached, a Memcached patch, provides this functionallitySource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesnoyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelyes infousing SASL (Simple Authentication and Security Layer) protocolFine grained access control via users, groups and roles

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More resources
Google Cloud BigtableKineticaMemcachedSingleStore infoformer name was MemSQL
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