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DBMS > Apache Phoenix vs. BigObject vs. Datastax Enterprise vs. DuckDB

System Properties Comparison Apache Phoenix vs. BigObject vs. Datastax Enterprise vs. DuckDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBigObject  Xexclude from comparisonDatastax Enterprise  Xexclude from comparisonDuckDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAnalytic DBMS for real-time computations and queriesDataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.An embeddable, in-process, column-oriented SQL OLAP RDBMS
Primary database modelRelational DBMSRelational DBMS infoa hierachical model (tree) can be imposedWide column storeRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.19
Rank#329  Overall
#146  Relational DBMS
Score5.93
Rank#56  Overall
#4  Wide column stores
Score4.63
Rank#69  Overall
#37  Relational DBMS
Websitephoenix.apache.orgbigobject.iowww.datastax.com/­products/­datastax-enterpriseduckdb.org
Technical documentationphoenix.apache.orgdocs.bigobject.iodocs.datastax.comduckdb.org/­docs
DeveloperApache Software FoundationBigObject, Inc.DataStax
Initial release2014201520112018
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20196.8, April 20201.0.0, June 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availablecommercialOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.
Implementation languageJavaJavaC++
Server operating systemsLinux
Unix
Windows
Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
OS X
server-less
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL-like DML and DDL statements (CQL); Spark SQLyes
APIs and other access methodsJDBCfluentd
ODBC
RESTful HTTP API
Proprietary protocol infoCQL (Cassandra Query Language)
TinkerPop Gremlin infowith DSE Graph
Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
Server-side scripts infoStored proceduresuser defined functionsLuanono
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infono "single point of failure"none
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneconfigurable replication factor, datacenter aware, advanced replication for edge computingnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencynoneImmediate Consistency
Tunable Consistency infoconsistency level can be individually decided with each write operation
Immediate Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono infoAtomicity and isolation are supported for single operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes, multi-version concurrency control (MVCC)
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.yesyesyesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoAccess rights for users can be defined per objectno
More information provided by the system vendor
Apache PhoenixBigObjectDatastax EnterpriseDuckDB
Specific characteristicsDataStax Enterprise is scale-out data infrastructure for enterprises that need to...
» more
Competitive advantagesSupporting the following application requirements: Zero downtime - Built on Apache...
» more
Typical application scenariosApplications that must be massively and linearly scalable with 100% uptime and able...
» more
Key customersCapital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
» more
Market metricsAmong the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
» more
Licensing and pricing modelsAnnual subscription
» more

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More resources
Apache PhoenixBigObjectDatastax EnterpriseDuckDB
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