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DBMS > Google Cloud Bigtable vs. Memcached vs. Oracle Berkeley DB vs. Spark SQL vs. TigerGraph

System Properties Comparison Google Cloud Bigtable vs. Memcached vs. Oracle Berkeley DB vs. Spark SQL vs. TigerGraph

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMemcached  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTigerGraph  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.In-memory key-value store, originally intended for cachingWidely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelKey-value store
Wide column store
Key-value storeKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score19.42
Rank#32  Overall
#4  Key-value stores
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitecloud.google.com/­bigtablewww.memcached.orgwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlwww.tigergraph.com
Technical documentationcloud.google.com/­bigtable/­docsgithub.com/­memcached/­memcached/­wikidocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.tigergraph.com
DeveloperGoogleDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalOracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software Foundation
Initial release20152003199420142017
Current release1.6.25, March 202418.1.40, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSD licenseOpen Source infocommercial license availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC, Java, C++ (depending on the Berkeley DB edition)ScalaC++
Server operating systemshostedFreeBSD
Linux
OS X
Unix
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenononoyesyes
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.noyes infoonly with the Berkeley DB XML editionnono
Secondary indexesnonoyesno
SQL infoSupport of SQLnonoyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsSQL-like query language (GSQL)
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Proprietary protocolJDBC
ODBC
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Java
Python
R
Scala
C++
Java
Server-side scripts infoStored proceduresnonononoyes
Triggersnonoyes infoonly for the SQL APInono
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesnone infoRepcached, a Memcached patch, provides this functionallitySource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynonononoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesnoyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infousing SASL (Simple Authentication and Security Layer) protocolnonoRole-based access control

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More resources
Google Cloud BigtableMemcachedOracle Berkeley DBSpark SQLTigerGraph
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