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DBMS > Apache Impala vs. Blazegraph vs. Google Cloud Datastore vs. Hypertable

System Properties Comparison Apache Impala vs. Blazegraph vs. Google Cloud Datastore vs. Hypertable

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBlazegraph  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHypertable  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAn open source BigTable implementation based on distributed file systems such as Hadoop
Primary database modelRelational DBMSGraph DBMS
RDF store
Document storeWide column store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score4.36
Rank#72  Overall
#12  Document stores
Websiteimpala.apache.orgblazegraph.comcloud.google.com/­datastore
Technical documentationimpala.apache.org/­impala-docs.htmlwiki.blazegraph.comcloud.google.com/­datastore/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaBlazegraphGoogleHypertable Inc.
Initial release2013200620082009
Current release4.1.0, June 20222.1.5, March 20190.9.8.11, March 2016
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoextended commercial license availablecommercialOpen Source infoGNU version 3. Commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++
Server operating systemsLinuxLinux
OS X
Windows
hostedLinux
OS X
Windows infoan inofficial Windows port is available
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infoRDF literal typesyes, details hereno
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
Secondary indexesyesyesyesrestricted infoonly exact value or prefix value scans
SQL infoSupport of SQLSQL-like DML and DDL statementsSPARQL is used as query languageSQL-like query language (GQL)no
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ API
Thrift
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesusing Google App Engineno
TriggersnonoCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication using Paxosselectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infousing Google Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in Graphsyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosSecurity and Authentication via Web Application Container (Tomcat, Jetty)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
Apache ImpalaBlazegraphGoogle Cloud DatastoreHypertable
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