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DBMS > EsgynDB vs. Google Cloud Bigtable vs. SQL.JS vs. Vertica

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. SQL.JS vs. Vertica

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSQL.JS  Xexclude from comparisonVertica infoOpenText™ Vertica™  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.Port of SQLite to JavaScriptCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.63
Rank#241  Overall
#112  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablesql.js.orgwww.vertica.com
Technical documentationcloud.google.com/­bigtable/­docssql.js.org/­documentation/­index.htmlvertica.com/­documentation
DeveloperEsgynGoogleAlon Zakai infoenhancements implemented by othersOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015201520122005
Current release12.0.3, January 2023
License infoCommercial or Open SourcecommercialcommercialOpen Sourcecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaScriptC++
Server operating systemsLinuxhostedserver-less, requires a JavaScript environment (browser, Node.js)Linux
Data schemeyesschema-freeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesnoyesyes
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 Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesnoyes infoSQL-92 is not fully supportedFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JavaScript APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
JavaScriptC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresJava Stored Proceduresnonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnononoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonehorizontal partitioning, hierarchical partitioning
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 zonesnoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)noneImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesno infoexcept by serializing a db to a fileyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
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)nofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
EsgynDBGoogle Cloud BigtableSQL.JSVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more

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EsgynDBGoogle Cloud BigtableSQL.JSVertica infoOpenText™ Vertica™
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