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DBMS > Atos Standard Common Repository vs. Databricks vs. QuestDB vs. Weaviate

System Properties Comparison Atos Standard Common Repository vs. Databricks vs. QuestDB vs. Weaviate

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonQuestDB  Xexclude from comparisonWeaviate  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A high performance open source SQL database for time series dataAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelDocument store
Key-value store
Document store
Relational DBMS
Time Series DBMSVector DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score1.73
Rank#143  Overall
#5  Vector DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comquestdb.iogithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.databricks.comquestdb.io/­docsweaviate.io/­developers/­weaviate
DeveloperAtos Convergence CreatorsDatabricksQuestDB Technology IncWeaviate B.V.
Initial release2016201320142019
Current release17031.19, May 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava (Zero-GC), C++, RustGo
Server operating systemsLinuxhostedLinux
macOS
Windows
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)yes infoschema-free via InfluxDB Line Protocolyes, maps to GraphQL interface
Typing infopredefined data types such as float or dateoptionalyesyes 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.yesyesnono
Secondary indexesyesyesnoyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLnowith Databricks SQLSQL with time-series extensionsGraphQL is used as query language
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindingsPython
R
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnono
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionhorizontal partitioning (by timestamps)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesSource-replica replication with eventual consistencyyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infothrough memory mapped filesyes
User concepts infoAccess controlLDAP bind authenticationAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
Atos Standard Common RepositoryDatabricksQuestDBWeaviate
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Relational model with native time series support Column-based storage and time partitioned...
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Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
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Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
As a database supporting the development of generative AI and semantic search applications...
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Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» 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 modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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