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DBMS > Amazon DynamoDB vs. Apache Impala vs. Databricks vs. Hypertable vs. InterSystems Caché

System Properties Comparison Amazon DynamoDB vs. Apache Impala vs. Databricks vs. Hypertable vs. InterSystems Caché

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonHypertable  Xexclude from comparisonInterSystems Caché  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudAnalytic DBMS for HadoopThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.An open source BigTable implementation based on distributed file systems such as HadoopA multi-model DBMS and application server
Primary database modelDocument store
Key-value store
Relational DBMSDocument store
Relational DBMS
Wide column storeKey-value store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.07
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Websiteaws.amazon.com/­dynamodbimpala.apache.orgwww.databricks.comwww.intersystems.com/­products/­cache
Technical documentationdocs.aws.amazon.com/­dynamodbimpala.apache.org/­impala-docs.htmldocs.databricks.comdocs.intersystems.com
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksHypertable Inc.InterSystems
Initial release20122013201320091997
Current release4.1.0, June 20220.9.8.11, March 20162018.1.4, May 2020
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache Version 2commercialOpen Source infoGNU version 3. Commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemshostedLinuxhostedLinux
OS X
Windows infoan inofficial Windows port is available
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesFlexible Schema (defined schema, partial schema, schema free)schema-freedepending on used data model
Typing infopredefined data types such as float or dateyesyesnoyes
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.noyesyes
Secondary indexesyesyesyesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementswith Databricks SQLnoyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
C++ API
Thrift
.NET Client API
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBCPython
R
Scala
C++
Java
Perl
PHP
Python
Ruby
C#
C++
Java
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesnoyes
Triggersyes infoby integration with AWS Lambdanonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factoryesselectable replication factor on file system levelSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
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 regionnoACIDnoACID
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.nonoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess rights for users, groups and roles
More information provided by the system vendor
Amazon DynamoDBApache ImpalaDatabricksHypertableInterSystems Caché
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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