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DBMS > AnzoGraph DB vs. Apache Impala vs. Brytlyt vs. Google Cloud Bigtable vs. TimescaleDB

System Properties Comparison AnzoGraph DB vs. Apache Impala vs. Brytlyt vs. Google Cloud Bigtable vs. TimescaleDB

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache Impala  Xexclude from comparisonBrytlyt  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationAnalytic DBMS for HadoopScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLGoogle'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 modelGraph DBMS
RDF store
Relational DBMSRelational DBMSKey-value store
Wide column store
Time Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.29
Rank#288  Overall
#131  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitecambridgesemantics.com/­anzographimpala.apache.orgbrytlyt.iocloud.google.com/­bigtablewww.timescale.com
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmimpala.apache.org/­impala-docs.htmldocs.brytlyt.iocloud.google.com/­bigtable/­docsdocs.timescale.com
DeveloperCambridge SemanticsApache Software Foundation infoApache top-level project, originally developed by ClouderaBrytlytGoogleTimescale
Initial release20182013201620152017
Current release2.3, January 20214.1.0, June 20225.0, August 20232.15.0, May 2024
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2commercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++ and CUDAC
Server operating systemsLinuxLinuxLinux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeSchema-free and OWL/RDFS-schema supportyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnonumerics, 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 infospecific XML-type available, but no XML query functionality.noyes
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like DML and DDL statementsyesnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (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++
Java
Python
All languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Perl
Python
Tcl
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 functions and aggregatesyes infouser defined functions and integration of map-reduceuser defined functions infoin PL/pgSQLnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusterselectable replication factorSource-replica replicationInternal 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 methodsKerberos/HDFS data loadingyes infoquery execution via MapReducenoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDAtomic single-row operationsACID
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.yesnonono
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAccess 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
AnzoGraph DBApache ImpalaBrytlytGoogle Cloud BigtableTimescaleDB
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