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DBMS > Apache Phoenix vs. EJDB vs. Google Cloud Bigtable vs. TimescaleDB

System Properties Comparison Apache Phoenix vs. EJDB vs. Google Cloud Bigtable vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonEJDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSDocument storeKey-value store
Wide column store
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.31
Rank#296  Overall
#44  Document stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitephoenix.apache.orggithub.com/­Softmotions/­ejdbcloud.google.com/­bigtablewww.timescale.com
Technical documentationphoenix.apache.orggithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­bigtable/­docsdocs.timescale.com
DeveloperApache Software FoundationSoftmotionsGoogleTimescale
Initial release2014201220152017
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20192.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGPLv2commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC
Server operating systemsLinux
Unix
Windows
server-lesshostedLinux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyes
Secondary indexesyesnonoyes
SQL infoSupport of SQLyesnonoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBCin-process shared librarygRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneInternal replication in Colossus, and regional replication between two clusters in different zonesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynono infotypically not needed, however similar functionality with collection joins possiblenoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyes
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.yesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Apache PhoenixEJDBGoogle Cloud BigtableTimescaleDB
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