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DBMS > Google Cloud Bigtable vs. Memcached vs. Microsoft Azure Synapse Analytics vs. Sadas Engine vs. XTDB

System Properties Comparison Google Cloud Bigtable vs. Memcached vs. Microsoft Azure Synapse Analytics vs. Sadas Engine vs. XTDB

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMemcached  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSadas Engine  Xexclude from comparisonXTDB infoformerly named Crux  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 cachingElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelKey-value store
Wide column store
Key-value storeRelational DBMSRelational DBMSDocument store
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
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websitecloud.google.com/­bigtablewww.memcached.orgazure.microsoft.com/­services/­synapse-analyticswww.sadasengine.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationcloud.google.com/­bigtable/­docsgithub.com/­memcached/­memcached/­wikidocs.microsoft.com/­azure/­synapse-analyticswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationwww.xtdb.com/­docs
DeveloperGoogleDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicrosoftSADAS s.r.l.Juxt Ltd.
Initial release20152003201620062019
Current release1.6.25, March 20248.01.19, September 2021
License infoCommercial or Open SourcecommercialOpen Source infoBSD licensecommercialcommercial infofree trial version availableOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++C++Clojure
Server operating systemshostedFreeBSD
Linux
OS X
Unix
Windows
hostedAIX
Linux
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeschema-freeyesyesschema-free
Typing infopredefined data types such as float or datenonoyesyesyes, extensible-data-notation format
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.nononono
Secondary indexesnonoyesyesyes
SQL infoSupport of SQLnonoyesyeslimited SQL, making use of Apache Calcite
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Proprietary protocolADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
HTTP REST
JDBC
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C#
Java
PHP
.Net
C
C#
C++
Groovy
Java
PHP
Python
Clojure
Java
Server-side scripts infoStored proceduresnonoTransact SQLnono
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding, horizontal partitioninghorizontal partitioningnone
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 functionallityyesnoneyes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesnoyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infomanaged by 'Learn by Usage'
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) protocolyesAccess rights for users, groups and roles according to SQL-standard

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More resources
Google Cloud BigtableMemcachedMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSadas EngineXTDB infoformerly named Crux
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