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DBMS > Apache Phoenix vs. Google Cloud Spanner vs. InfinityDB vs. QuestDB

System Properties Comparison Apache Phoenix vs. Google Cloud Spanner vs. InfinityDB vs. QuestDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonInfinityDB  Xexclude from comparisonQuestDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A Java embedded Key-Value Store which extends the Java Map interfaceA high performance open source SQL database for time series data
Primary database modelRelational DBMSRelational DBMSKey-value storeTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.00
Rank#378  Overall
#57  Key-value stores
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Websitephoenix.apache.orgcloud.google.com/­spannerboilerbay.comquestdb.io
Technical documentationphoenix.apache.orgcloud.google.com/­spanner/­docsboilerbay.com/­infinitydb/­manualquestdb.io/­docs
DeveloperApache Software FoundationGoogleBoiler Bay Inc.QuestDB Technology Inc
Initial release2014201720022014
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache 2.0
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 languageJavaJavaJava (Zero-GC), C++, Rust
Server operating systemsLinux
Unix
Windows
hostedAll OS with a Java VMLinux
macOS
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes infoschema-free via InfluxDB Line Protocol
Typing infopredefined data types such as float or dateyesyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes
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 indexesyesyesno infomanual creation possible, using inversions based on multi-value capabilityno
SQL infoSupport of SQLyesyes infoQuery statements complying to ANSI 2011noSQL with time-series extensions
APIs and other access methodsJDBCgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
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
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Java
JavaScript (Node.js)
Python
JavaC infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Server-side scripts infoStored proceduresuser defined functionsnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonehorizontal partitioning (by timestamps)
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication with 3 replicas for regional instances.noneSource-replica replication with eventual consistency
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityno infomanual creation possible, using inversions based on multi-value capabilityno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoStrict serializable isolationACID infoOptimistic locking for transactions; no isolation for bulk loadsACID for single-table writes
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.yesnonoyes infothrough memory mapped files
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no
More information provided by the system vendor
Apache PhoenixGoogle Cloud SpannerInfinityDBQuestDB
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache PhoenixGoogle Cloud SpannerInfinityDBQuestDB
DB-Engines blog posts

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Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Azure #HDInsight Apache Phoenix now supports Zeppelin
16 August 2018, azure.microsoft.com

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

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27 March 2017, SDTimes.com

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28 June 2016, ADT Magazine

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