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DBMS > Atos Standard Common Repository vs. FeatureBase vs. InfinityDB vs. QuestDB vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. FeatureBase vs. InfinityDB vs. QuestDB vs. Spark SQL

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonFeatureBase  Xexclude from comparisonInfinityDB  Xexclude from comparisonQuestDB  Xexclude from comparisonSpark SQL  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 networksReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.A Java embedded Key-Value Store which extends the Java Map interfaceA high performance open source SQL database for time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSKey-value storeTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#309  Overall
#139  Relational DBMS
Score0.00
Rank#378  Overall
#57  Key-value stores
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.featurebase.comboilerbay.comquestdb.iospark.apache.org/­sql
Technical documentationdocs.featurebase.comboilerbay.com/­infinitydb/­manualquestdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsMolecula and Pilosa Open Source ContributorsBoiler Bay Inc.QuestDB Technology IncApache Software Foundation
Initial release20162017200220142014
Current release17032022, May 20224.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoJavaJava (Zero-GC), C++, RustScala
Server operating systemsLinuxLinux
macOS
All OS with a Java VMLinux
macOS
Windows
Linux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateoptionalyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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.yesnononono
Secondary indexesyesnono infomanual creation possible, using inversions based on multi-value capabilitynono
SQL infoSupport of SQLnoSQL queriesnoSQL with time-series extensionsSQL-like DML and DDL statements
APIs and other access methodsLDAPgRPC
JDBC
Kafka Connector
ODBC
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsJava
Python
JavaC infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
Python
R
Scala
Server-side scripts infoStored proceduresnononono
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingnonehorizontal partitioning (by timestamps)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnoneSource-replica replication with eventual consistencynone
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 Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integritynoyesno infomanual creation possible, using inversions based on multi-value capabilitynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsyesACID infoOptimistic locking for transactions; no isolation for bulk loadsACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes, using Linux fsyncyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes infothrough memory mapped filesno
User concepts infoAccess controlLDAP bind authenticationnono
More information provided by the system vendor
Atos Standard Common RepositoryFeatureBaseInfinityDBQuestDBSpark SQL
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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Atos Standard Common RepositoryFeatureBaseInfinityDBQuestDBSpark SQL
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