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DBMS > Badger vs. Databend vs. dBASE vs. Google Cloud Bigtable vs. Lovefield

System Properties Comparison Badger vs. Databend vs. dBASE vs. Google Cloud Bigtable vs. Lovefield

Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatabend  Xexclude from comparisondBASE  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonLovefield  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexitydBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Embeddable relational database for web apps written in pure JavaScript
Primary database modelKey-value storeRelational DBMSRelational DBMSKey-value store
Wide column store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#331  Overall
#49  Key-value stores
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score10.34
Rank#44  Overall
#28  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.29
Rank#293  Overall
#133  Relational DBMS
Websitegithub.com/­dgraph-io/­badgergithub.com/­datafuselabs/­databend
www.databend.com
www.dbase.comcloud.google.com/­bigtablegoogle.github.io/­lovefield
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.databend.comwww.dbase.com/­support/­knowledgebasecloud.google.com/­bigtable/­docsgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.md
DeveloperDGraph LabsDatabend LabsAsthon TateGoogleGoogle
Initial release20172021197920152014
Current release1.0.59, April 2023dBASE 2019, 20192.1.12, February 2017
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoRustJavaScript
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hosted
Linux
macOS
DOS infodBase Classic
Windows infodBase Pro
hostedserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, Safari
Data schemeschema-freeyesyesschema-freeyes
Typing infopredefined data types such as float or datenoyesyesnoyes
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 indexesnonoyesnoyes
SQL infoSupport of SQLnoyesnonoSQL-like query language infovia JavaScript builder pattern
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
none infoThe IDE can access other DBMS or ODBC-sources.gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesGoGo
Java
JavaScript (Node.js)
Python
Rust
dBase proprietary IDEC#
C++
Go
Java
JavaScript (Node.js)
Python
JavaScript
Server-side scripts infoStored proceduresnonono infoThe IDE can access stored procedures in other database systems.nono
TriggersnonononoUsing read-only observers
Partitioning methods infoMethods for storing different data on different nodesnonenonenoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenonenoneInternal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesno infonot for dBase internal data, but IDE does support transactions when accessing external DBMSAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Database
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infousing MemoryDB
User concepts infoAccess controlnoUsers with fine-grained authorization concept, user rolesAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
BadgerDatabenddBASEGoogle Cloud BigtableLovefield
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