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DBMS > Apache Phoenix vs. EsgynDB vs. Google Cloud Datastore vs. TigerGraph vs. Weaviate

System Properties Comparison Apache Phoenix vs. EsgynDB vs. Google Cloud Datastore vs. TigerGraph vs. Weaviate

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTigerGraph  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-timeAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSRelational DBMSDocument storeGraph DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score1.83
Rank#139  Overall
#13  Graph DBMS
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websitephoenix.apache.orgwww.esgyn.cncloud.google.com/­datastorewww.tigergraph.comgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationphoenix.apache.orgcloud.google.com/­datastore/­docsdocs.tigergraph.comweaviate.io/­developers/­weaviate
DeveloperApache Software FoundationEsgynGoogleWeaviate B.V.
Initial release20142015200820172019
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.19, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercialOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, JavaC++Go
Server operating systemsLinux
Unix
Windows
LinuxhostedLinux
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyesyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes infostring, int, float, geo point, date, cross reference, fuzzy references
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.nonononono
Secondary indexesyesyesyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLyesyesSQL-like query language (GQL)SQL-like query language (GSQL)GraphQL is used as query language
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresuser defined functionsJava Stored Proceduresusing Google App Engineyesno
TriggersnonoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication between multi datacentersMulti-source replication using Paxosyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesyes infousing Google Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnononoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
Apache PhoenixEsgynDBGoogle Cloud DatastoreTigerGraphWeaviate
Specific characteristicsWeaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantagesFlexible deployment - Free, open source or fully-managed cloud vector database service...
» more
Typical application scenariosAs a database supporting the development of generative AI and semantic search applications...
» more
Key customersAll companies that have data. ​
» more
Market metricsAs of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsWeaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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More resources
Apache PhoenixEsgynDBGoogle Cloud DatastoreTigerGraphWeaviate
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