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DBMS > Google Cloud Bigtable vs. LevelDB vs. Postgres-XL vs. Sqrrl vs. Tkrzw

System Properties Comparison Google Cloud Bigtable vs. LevelDB vs. Postgres-XL vs. Sqrrl vs. Tkrzw

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonLevelDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSqrrl  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresAdaptable, secure NoSQL built on Apache AccumuloA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelKey-value store
Wide column store
Key-value storeRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Key-value store
Secondary database modelsDocument store
Spatial 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
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitecloud.google.com/­bigtablegithub.com/­google/­leveldbwww.postgres-xl.orgsqrrl.comdbmx.net/­tkrzw
Technical documentationcloud.google.com/­bigtable/­docsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdwww.postgres-xl.org/­documentation
DeveloperGoogleGoogleAmazon infooriginally Sqrrl Data, Inc.Mikio Hirabayashi
Initial release201520112014 infosince 2012, originally named StormDB20122020
Current release1.23, February 202110 R1, October 20180.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoMozilla public licensecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CJavaC++
Server operating systemshostedIllumos
Linux
OS X
Windows
Linux
macOS
LinuxLinux
macOS
Data schemeschema-freeschema-freeyesschema-freeschema-free
Typing infopredefined data types such as float or datenonoyesyesno
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.nonoyes infoXML type, but no XML query functionalityno
Secondary indexesnonoyesyes
SQL infoSupport of SQLnonoyes infodistributed, parallel query executionnono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnonouser defined functionsnono
Triggersnonoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioningSharding infomaking use of Hadoopnone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesnoneselectable replication factor infomaking use of Hadoopnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoyesno
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 ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsnoACID infoMVCCAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standardCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)no

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More resources
Google Cloud BigtableLevelDBPostgres-XLSqrrlTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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