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DBMS > Apache Phoenix vs. HarperDB vs. InfinityDB vs. Microsoft Azure Synapse Analytics

System Properties Comparison Apache Phoenix vs. HarperDB vs. InfinityDB vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHarperDB  Xexclude from comparisonInfinityDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseHarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.A Java embedded Key-Value Store which extends the Java Map interfaceElastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelRelational DBMSDocument storeKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#125  Overall
#59  Relational DBMS
Score0.55
Rank#243  Overall
#38  Document stores
Score0.00
Rank#383  Overall
#59  Key-value stores
Score18.98
Rank#31  Overall
#19  Relational DBMS
Websitephoenix.apache.orgwww.harperdb.ioboilerbay.comazure.microsoft.com/­services/­synapse-analytics
Technical documentationphoenix.apache.orgdocs.harperdb.io/­docsboilerbay.com/­infinitydb/­manualdocs.microsoft.com/­azure/­synapse-analytics
DeveloperApache Software FoundationHarperDBBoiler Bay Inc.Microsoft
Initial release2014201720022016
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.1, August 20214.0
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaNode.jsJavaC++
Server operating systemsLinux
Unix
Windows
Linux
OS X
All OS with a Java VMhosted
Data schemeyes infolate-bound, schema-on-read capabilitiesdynamic schemayes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyes 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 capabilityyes
SQL infoSupport of SQLyesSQL-like data manipulation statementsnoyes
APIs and other access methodsJDBCJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
ADO.NET
JDBC
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
JavaC#
Java
PHP
Server-side scripts infoStored proceduresuser defined functionsCustom Functions infosince release 3.1noTransact SQL
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusternoneSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infothe nodes on which a table resides can be definednoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integritynonono infomanual creation possible, using inversions based on multi-value capabilityno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsACID infoOptimistic locking for transactions; no isolation for bulk loadsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users and rolesnoyes

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More resources
Apache PhoenixHarperDBInfinityDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
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