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DBMS > Google Cloud Bigtable vs. KeyDB vs. Microsoft Azure Synapse Analytics vs. Sqrrl

System Properties Comparison Google Cloud Bigtable vs. KeyDB vs. Microsoft Azure Synapse Analytics vs. Sqrrl

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonKeyDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been 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.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelKey-value store
Wide column store
Key-value storeRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column 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
Score0.71
Rank#226  Overall
#33  Key-value stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websitecloud.google.com/­bigtablegithub.com/­Snapchat/­KeyDB
keydb.dev
azure.microsoft.com/­services/­synapse-analyticssqrrl.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.keydb.devdocs.microsoft.com/­azure/­synapse-analytics
DeveloperGoogleEQ Alpha Technology Ltd.MicrosoftAmazon infooriginally Sqrrl Data, Inc.
Initial release2015201920162012
License infoCommercial or Open SourcecommercialOpen Source infoBSD-3commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Java
Server operating systemshostedLinuxhostedLinux
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenopartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyesyes
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 indexesnoyes infoby using the Redis Search moduleyesyes
SQL infoSupport of SQLnonoyesno
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Proprietary protocol infoRESP - REdis Serialization ProtocoADO.NET
JDBC
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
C#
Java
PHP
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresnoLuaTransact SQLno
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioningSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
yesselectable replication factor infomaking use of Hadoop
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)Eventual Consistency
Strong eventual consistency with CRDTs
Immediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsOptimistic locking, atomic execution of commands blocks and scriptsACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access control and ACLyesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Google Cloud BigtableKeyDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSqrrl
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