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DBMS > Google Cloud Bigtable vs. HBase vs. LevelDB vs. Sqrrl vs. Tkrzw

System Properties Comparison Google Cloud Bigtable vs. HBase vs. LevelDB vs. Sqrrl vs. Tkrzw

Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHBase  Xexclude from comparisonLevelDB  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.Wide-column store based on Apache Hadoop and on concepts of BigTableEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesAdaptable, 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
Wide column storeKey-value storeDocument store
Graph DBMS
Key-value store
Wide column store
Key-value 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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score2.35
Rank#111  Overall
#19  Key-value stores
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitecloud.google.com/­bigtablehbase.apache.orggithub.com/­google/­leveldbsqrrl.comdbmx.net/­tkrzw
Technical documentationcloud.google.com/­bigtable/­docshbase.apache.org/­book.htmlgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetGoogleAmazon infooriginally Sqrrl Data, Inc.Mikio Hirabayashi
Initial release20152008201120122020
Current release2.3.4, January 20211.23, February 20210.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoBSDcommercialOpen 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 languageJavaC++JavaC++
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
Illumos
Linux
OS X
Windows
LinuxLinux
macOS
Data schemeschema-freeschema-free, schema definition possibleschema-freeschema-freeschema-free
Typing infopredefined data types such as float or datenooptions to bring your own types, AVROnoyesno
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 indexesnononoyes
SQL infoSupport of SQLnonononono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
RESTful HTTP API
Thrift
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
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 proceduresnoyes infoCoprocessors in Javanonono
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding 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 zonesMulti-source replication
Source-replica replication
noneselectable replication factor infomaking use of Hadoopnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnoyesno
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 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 integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsSingle row ACID (across millions of columns)noAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)no

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More resources
Google Cloud BigtableHBaseLevelDBSqrrlTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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