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DBMS > Apache Phoenix vs. etcd vs. H2 vs. IBM Db2 Event Store vs. TimescaleDB

System Properties Comparison Apache Phoenix vs. etcd vs. H2 vs. IBM Db2 Event Store vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonetcd  Xexclude from comparisonH2  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA distributed reliable key-value storeFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Distributed Event Store optimized for Internet of Things use casesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSKey-value storeRelational DBMSEvent Store
Time Series DBMS
Time Series DBMS
Secondary database modelsSpatial DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score8.13
Rank#49  Overall
#31  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitephoenix.apache.orgetcd.io
github.com/­etcd-io/­etcd
www.h2database.comwww.ibm.com/­products/­db2-event-storewww.timescale.com
Technical documentationphoenix.apache.orgetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
www.h2database.com/­html/­main.htmlwww.ibm.com/­docs/­en/­db2-event-storedocs.timescale.com
DeveloperApache Software FoundationThomas MuellerIBMTimescale
Initial release2014200520172017
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.4, August 20192.2.220, July 20232.02.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infodual-licence (Mozilla public license, Eclipse public license)commercial infofree developer edition availableOpen 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 languageJavaGoJavaC and C++C
Server operating systemsLinux
Unix
Windows
FreeBSD
Linux
Windows infoexperimental
All OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionLinux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesnumerics, 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.nonononoyes
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLyesnoyesyes infothrough the embedded Spark runtimeyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBCgRPC
JSON over HTTP
JDBC
ODBC
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
JavaC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsnoJava Stored Procedures and User-Defined Functionsyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyes, watching key changesyesnoyes
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
Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.With clustering: 2 database servers on different computers operate on identical copies of a databaseActive-active shard replicationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)No - written data is immutableyes
Durability infoSupport for making data persistentyesyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynofine grained access rights according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Apache PhoenixetcdH2IBM Db2 Event StoreTimescaleDB
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