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DBMS > Altibase vs. Apache Phoenix vs. Google Cloud Spanner vs. HugeGraph vs. Sadas Engine

System Properties Comparison Altibase vs. Apache Phoenix vs. Google Cloud Spanner vs. HugeGraph vs. Sadas Engine

Editorial information provided by DB-Engines
NameAltibase  Xexclude from comparisonApache Phoenix  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHugeGraph  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionAn enterprise grade, high-performance RDBMSA 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 fast-speed and highly-scalable Graph DBMSSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelRelational DBMSRelational DBMSRelational DBMSGraph DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.07
Rank#186  Overall
#87  Relational DBMS
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Websitealtibase.comphoenix.apache.orgcloud.google.com/­spannergithub.com/­hugegraph
hugegraph.apache.org
www.sadasengine.com
Technical documentationgithub.com/­ALTIBASE/­Documents/­tree/­master/­Manualsphoenix.apache.orgcloud.google.com/­spanner/­docshugegraph.apache.org/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperAltibaseApache Software FoundationGoogleBaiduSADAS s.r.l.
Initial release19992014201720182006
Current releasev7.3, 2023, August 20235.0-HBase2, July 2018 and 4.15-HBase1, December 20190.98.0
License infoCommercial or Open Sourcecommercial infoOpen source edition discontinued with March 2023Open Source infoApache Version 2.0commercialOpen Source infoApache Version 2.0commercial infofree trial version available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaJavaC++
Server operating systemsAIX
HP-UX
Linux
Linux
Unix
Windows
hostedLinux
macOS
Unix
AIX
Linux
Windows
Data schemeyesyes infolate-bound, schema-on-read capabilitiesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nonononono
Secondary indexesyesyesyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLANSI SQL-92yesyes infoQuery statements complying to ANSI 2011noyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
JDBCgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
Proprietary protocol
Supported programming languagesC
C++
Java
C
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Java
JavaScript (Node.js)
Python
Groovy
Java
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresstored procedures and stored functionsuser defined functionsnoasynchronous Gremlin script jobsno
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBasehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Multi-source replication with 3 replicas for regional instances.yes infodepending on used storage backend, e.g. Cassandra and HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoHadoop integrationyes infousing Google Cloud Dataflowvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoStrict serializable isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyesyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess 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)Users, roles and permissionsAccess rights for users, groups and roles according to SQL-standard

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More resources
AltibaseApache PhoenixGoogle Cloud SpannerHugeGraphSadas Engine
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