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DBMS > EsgynDB vs. Google Cloud Bigtable vs. LevelDB vs. Pinecone

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. LevelDB vs. Pinecone

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonLevelDB  Xexclude from comparisonPinecone  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle'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 valuesA managed, cloud-native vector database
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value storeVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score2.33
Rank#111  Overall
#19  Key-value stores
Score3.02
Rank#87  Overall
#3  Vector DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablegithub.com/­google/­leveldbwww.pinecone.io
Technical documentationcloud.google.com/­bigtable/­docsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddocs.pinecone.io/­docs/­overview
DeveloperEsgynGoogleGooglePinecone Systems, Inc
Initial release2015201520112019
Current release1.23, February 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++
Server operating systemsLinuxhostedIllumos
Linux
OS X
Windows
hosted
Data schemeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesnonoString, Number, Boolean
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 indexesyesnono
SQL infoSupport of SQLyesnonono
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Python
Server-side scripts infoStored proceduresJava Stored Proceduresnono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
EsgynDBGoogle Cloud BigtableLevelDBPinecone
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