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DBMS > Amazon DynamoDB vs. AnzoGraph DB vs. Apache Impala vs. Faircom DB vs. Vertica

System Properties Comparison Amazon DynamoDB vs. AnzoGraph DB vs. Apache Impala vs. Faircom DB vs. Vertica

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonAnzoGraph DB  Xexclude from comparisonApache Impala  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationAnalytic DBMS for HadoopNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument store
Key-value store
Graph DBMS
RDF store
Relational DBMSKey-value store
Relational DBMS
Relational DBMS infoColumn oriented
Secondary database modelsDocument storeSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score77.72
Rank#16  Overall
#2  Document stores
#2  Key-value stores
Score0.31
Rank#295  Overall
#24  Graph DBMS
#13  RDF stores
Score15.06
Rank#39  Overall
#24  Relational DBMS
Score0.31
Rank#298  Overall
#42  Key-value stores
#137  Relational DBMS
Score11.76
Rank#44  Overall
#28  Relational DBMS
Websiteaws.amazon.com/­dynamodbcambridgesemantics.com/­anzographimpala.apache.orgwww.faircom.com/­products/­faircom-dbwww.vertica.com
Technical documentationdocs.aws.amazon.com/­dynamodbdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmimpala.apache.org/­impala-docs.htmldocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlvertica.com/­documentation
DeveloperAmazonCambridge SemanticsApache Software Foundation infoApache top-level project, originally developed by ClouderaFairCom CorporationOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20122018201319792005
Current release2.3, January 20214.1.0, June 2022V12, November 202012.0.3, January 2023
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercial infofree trial version availableOpen Source infoApache Version 2commercial infoRestricted, free version availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud serviceyesnononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ANSI C, C++C++
Server operating systemshostedLinuxLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
Data schemeschema-freeSchema-free and OWL/RDFS-schema supportyesschema free, schema optional, schema required, partial schema,Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesyes, ANSI SQL Types, JSON, typed binary structuresyes
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 indexesyesnoyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like DML and DDL statementsyes, ANSI SQL with proprietary extensionsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP APIApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
ODBC
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C++
Java
Python
All languages supporting JDBC/ODBC.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyes infouser defined functions and integration of map-reduceyes info.Net, JavaScript, C/C++yes, PostgreSQL PL/pgSQL, with minor differences
Triggersyes infoby integration with AWS Lambdanonoyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic shardingShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioninghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication in MPP-Clusterselectable replication factoryes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Multi-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Kerberos/HDFS data loadingyes infoquery execution via MapReducenono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate Consistency in MPP-ClusterEventual ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integritynono infonot needed in graphsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoACID across one or more tables within a single AWS account and regionACIDnotunable from ACID to Eventually ConsistentACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesYes, tunable from durable to delayed durability to in-memoryyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users and rolesAccess rights for users, groups and roles infobased on Apache Sentry and KerberosFine grained access rights according to SQL-standard with additional protections for filesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Amazon DynamoDBAnzoGraph DBApache ImpalaFaircom DB infoformerly c-treeACEVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Amazon DynamoDBAnzoGraph DBApache ImpalaFaircom DB infoformerly c-treeACEVertica infoOpenText™ Vertica™
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