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DBMS > AnzoGraph DB vs. eXtremeDB vs. Google Cloud Bigtable vs. Spark SQL

System Properties Comparison AnzoGraph DB vs. eXtremeDB vs. Google Cloud Bigtable vs. Spark SQL

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisoneXtremeDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationNatively in-memory DBMS with options for persistency, high-availability and clusteringGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Relational DBMS
Time Series DBMS
Key-value store
Wide column store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitecambridgesemantics.com/­anzographwww.mcobject.comcloud.google.com/­bigtablespark.apache.org/­sql
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmwww.mcobject.com/­docs/­extremedb.htmcloud.google.com/­bigtable/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCambridge SemanticsMcObjectGoogleApache Software Foundation
Initial release2018200120152014
Current release2.3, January 20218.2, 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialcommercialOpen 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 languageC and C++Scala
Server operating systemsLinuxAIX
HP-UX
Linux
macOS
Solaris
Windows
hostedLinux
OS X
Windows
Data schemeSchema-free and OWL/RDFS-schema supportyesschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
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.nono infosupport of XML interfaces availablenono
Secondary indexesnoyesnono
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.yes infowith the option: eXtremeSQLnoSQL-like DML and DDL statements
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Supported programming languagesC++
Java
Python
.Net
C
C#
C++
Java
Lua
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnono
Triggersnoyes infoby defining eventsnono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioning / shardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Internal replication in Colossus, and regional replication between two clusters in different zonesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityno infonot needed in graphsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
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.yesyesnono
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no
More information provided by the system vendor
AnzoGraph DBeXtremeDBGoogle Cloud BigtableSpark SQL
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more

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More resources
AnzoGraph DBeXtremeDBGoogle Cloud BigtableSpark SQL
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