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DBMS > GeoMesa vs. Google Cloud Bigtable vs. Oracle Berkeley DB vs. Qdrant vs. Warp 10

System Properties Comparison GeoMesa vs. Google Cloud Bigtable vs. Oracle Berkeley DB vs. Qdrant vs. Warp 10

Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonQdrant  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Widely used in-process key-value storeA high-performance vector database with neural network or semantic-based matchingTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelSpatial DBMSKey-value store
Wide column store
Key-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Vector DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score1.16
Rank#175  Overall
#6  Vector DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitewww.geomesa.orgcloud.google.com/­bigtablewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlgithub.com/­qdrant/­qdrant
qdrant.tech
www.warp10.io
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmlcloud.google.com/­bigtable/­docsdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlqdrant.tech/­documentationwww.warp10.io/­content/­02_Getting_started
DeveloperCCRi and othersGoogleOracle infooriginally developed by Sleepycat, which was acquired by OracleQdrantSenX
Initial release20142015199420212015
Current release4.0.5, February 202418.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialOpen Source infocommercial license availableOpen Source infoApache Version 2.0Open Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC, Java, C++ (depending on the Berkeley DB edition)RustJava
Server operating systemshostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Docker
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesschema-freeschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesnonoNumbers, Strings, Geo, Booleanyes
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 infoonly with the Berkeley DB XML editionnono
Secondary indexesyesnoyesyes infoKeywords, numberic ranges, geo, full-textno
SQL infoSupport of SQLnonoyes infoSQL interfaced based on SQLite is availablenono
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
HTTP API
Jupyter
WebSocket
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.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
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresnononoyes infoWarpScript
Triggersnonoyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerShardingnoneShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replicationCollection-level replicationselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency, tunable consistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.depending on storage layernoyesyesyes
User concepts infoAccess controlyes infodepending on the DBMS used for storageAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noKey-based authenticationMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
GeoMesaGoogle Cloud BigtableOracle Berkeley DBQdrantWarp 10
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