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DBMS > Google Cloud Bigtable vs. HarperDB vs. Hawkular Metrics vs. Oracle Berkeley DB

System Properties Comparison Google Cloud Bigtable vs. HarperDB vs. Hawkular Metrics vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonOracle Berkeley DB  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.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Widely used in-process key-value store
Primary database modelKey-value store
Wide column store
Document storeTime Series DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.60
Rank#244  Overall
#38  Document stores
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Websitecloud.google.com/­bigtablewww.harperdb.iowww.hawkular.orgwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationcloud.google.com/­bigtable/­docsdocs.harperdb.io/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperGoogleHarperDBCommunity supported by Red HatOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release2015201720141994
Current release3.1, August 202118.1.40, May 2020
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoApache 2.0Open Source infocommercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageNode.jsJavaC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedLinux
OS X
Linux
OS X
Windows
AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeschema-freedynamic schemaschema-freeschema-free
Typing infopredefined data types such as float or datenoyes infoJSON data typesyesno
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.nononoyes infoonly with the Berkeley DB XML edition
Secondary indexesnoyesnoyes
SQL infoSupport of SQLnoSQL-like data manipulation statementsnoyes infoSQL interfaced based on SQLite is available
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
HTTP REST
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Go
Java
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
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1nono
Triggersnonoyes infovia Hawkular Alertingyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterSharding infobased on Cassandranone
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes infothe nodes on which a table resides can be definedselectable replication factor infobased on CassandraSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsAtomic execution of specific operationsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesnono

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More resources
Google Cloud BigtableHarperDBHawkular MetricsOracle Berkeley DB
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