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DBMS > AntDB vs. Atos Standard Common Repository vs. GigaSpaces vs. Vertica vs. Weaviate

System Properties Comparison AntDB vs. Atos Standard Common Repository vs. GigaSpaces vs. Vertica vs. Weaviate

Editorial information provided by DB-Engines
NameAntDB  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonGigaSpaces  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonWeaviate  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionA scalable, multi-tenant, MPP-architectured RDBMS for OLTP and OLAP operations, highly compatible with OracleHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsCloud 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.An AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSDocument store
Key-value store
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMS infoColumn orientedVector DBMS
Secondary database modelsGraph DBMS
Search engine
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#317  Overall
#141  Relational DBMS
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Score1.52
Rank#153  Overall
#5  Vector DBMS
Websitewww.asiainfo.com/­en_us/­product_aisware_antdb_detail.htmlatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.gigaspaces.comwww.vertica.comgithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlvertica.com/­documentationweaviate.io/­developers/­weaviate
DeveloperAsiaInfo Technologies LimitedAtos Convergence CreatorsGigaspaces TechnologiesOpenText infopreviously Micro Focus and Hewlett PackardWeaviate B.V.
Initial release2016200020052019
Current release170315.5, September 202012.0.3, January 20231.19, May 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; Commercial licenses availablecommercial infoLimited community edition freeOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetC++Go
Server operating systemsLinuxLinux
macOS
Solaris
Windows
Linux
Data schemeyesSchema and schema-less with LDAP viewsschema-freeYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.yes, maps to GraphQL interface
Typing infopredefined data types such as float or dateyesoptionalyesyesyes 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.yesno infoXML can be used for describing objects metadatanono
Secondary indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.yes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLSQL2016 compliantnoSQL-99 for query and DML statementsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.GraphQL is used as query language
APIs and other access methodsJDBC
MySQL protocol compliant
ODBC
LDAPGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindings.Net
C++
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnoyesyes, PostgreSQL PL/pgSQL, with minor differencesno
Triggersyesyesyes, event driven architectureyes, called Custom Alertsno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardinghorizontal partitioning, hierarchical partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsno infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsACIDACIDno
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.yesyesyesnoyes
User concepts infoAccess controlLDAP bind authenticationRole-based access controlfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
AntDBAtos Standard Common RepositoryGigaSpacesVertica infoOpenText™ Vertica™Weaviate
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
As a database supporting the development of generative AI and semantic search applications...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
All companies that have data. ​
» more
Market metricsAs of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more
Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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More resources
AntDBAtos Standard Common RepositoryGigaSpacesVertica infoOpenText™ Vertica™Weaviate
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