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DBMS > Apache Impala vs. BoltDB vs. GraphDB vs. Teradata Aster

System Properties Comparison Apache Impala vs. BoltDB vs. GraphDB vs. Teradata Aster

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBoltDB  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopAn embedded key-value store for Go.Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.Platform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSKey-value storeGraph DBMS
RDF store
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score0.70
Rank#225  Overall
#31  Key-value stores
Score2.76
Rank#99  Overall
#8  Graph DBMS
#4  RDF stores
Websiteimpala.apache.orggithub.com/­boltdb/­boltwww.ontotext.com
Technical documentationimpala.apache.org/­impala-docs.htmlgraphdb.ontotext.com/­documentation
Social network pagesLinkedInTwitterYouTubeGitHubMedium
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaOntotextTeradata
Initial release2013201320002005
Current release4.1.0, June 202210.4, October 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMIT Licensecommercial infoSome plugins of GraphDB Workbench are open sourcedcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoJava
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
All OS with a Java VM
Linux
OS X
Windows
Linux
Data schemeyesschema-freeschema-free and OWL/RDFS-schema support; RDF shapesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesnoyesyes
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.nononoyes infoin Aster File Store
Secondary indexesyesnoyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnostored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCyes
APIs and other access methodsJDBC
ODBC
GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBCGo.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenowell-defined plugin interfaces; JavaScript server-side extensibilityR packages
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-source replicationyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyes infoConstraint checkingno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDACID
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.nonono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoDefault Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.fine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaBoltDBGraphDB infoformer name: OWLIMTeradata Aster
Specific characteristicsOntotext GraphDB is a semantic database engine that allows organizations to build...
» more
Competitive advantagesGraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more
Typical application scenariosMetadata enrichment and management, linked data publishing, semantic inferencing...
» more
Key customers​ GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more
Market metricsGraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more
Licensing and pricing modelsGraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more
News

GraphDB in Action: Using Semantics To Push The Envelope Of Software Engineering, Machine Learning, and E-Health Domains
11 September 2024

Accelerating End-to-end Knowledge Graph Solutions with Ontotext’s LinkedLifeData Inventory: The Case of Target Discovery
30 August 2024

Using Entity Linking to Turn Your Graph into a Knowledge Graph
23 August 2024

Considerations to Creating a Graph Center of Excellence: 5 Elements to Ensure Success
22 August 2024

The Power of Knowledge Graphs – A Chat with Perfect Memory and Ontotext
16 August 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache ImpalaBoltDBGraphDB infoformer name: OWLIMTeradata Aster
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