DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. Dgraph vs. GeoSpock vs. Trafodion

System Properties Comparison Apache Impala vs. Dgraph vs. GeoSpock vs. Trafodion

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDgraph  Xexclude from comparisonGeoSpock  Xexclude from comparisonTrafodion  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopDistributed and scalable native Graph DBMSSpatial and temporal data processing engine for extreme data scaleTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSGraph DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.53
Rank#152  Overall
#15  Graph DBMS
Websiteimpala.apache.orgdgraph.iogeospock.comtrafodion.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmldgraph.io/­docstrafodion.apache.org/­documentation.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDgraph Labs, Inc.GeoSpockApache Software Foundation, originally developed by HP
Initial release201320162014
Current release4.1.0, June 20222.0, September 20192.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoJava, JavascriptC++, Java
Server operating systemsLinuxLinux
OS X
Windows
hostedLinux
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyestemporal, categoricalyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoANSI SQL for query only (using Presto)yes
APIs and other access methodsJDBC
ODBC
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
JDBCADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoJava Stored Procedures
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesShardingyesAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSynchronous replication via Raftyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
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 Kerberosno infoPlanned for future releasesAccess rights for users can be defined per tablefine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaDgraphGeoSpockTrafodion
Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

Dgraph on AWS: Setting up a horizontally scalable graph database | Amazon Web Services
1 September 2020, AWS Blog

Popular Open Source GraphQL Company Dgraph Secures $6M in Seed Round with New Leadership
20 July 2022, PR Newswire

Dgraph launches Slash GraphQL, a GraphQL-native database Backend-as-a-Service
10 September 2020, TechCrunch

Dgraph Raises $6M in Seed Funding
20 July 2022, FinSMEs

Dgraph raises $11.5 million for scalable graph database solutions
31 July 2019, VentureBeat

provided by Google News

How GeoSpock is supercharging geospatial analytics
23 February 2021, ComputerWeekly.com

nChain Leads Investment Round in Extreme-scale Data Firm GeoSpock
2 October 2020, AlexaBlockchain

Imagining an ‘Everything Connected’ World With Geospock
20 June 2019, AWS Blog

Smart Cities, Autonomous Vehicles, Artificial General Intelligence Robotics: Q&A with Steve Marsh, GeoSpock
16 May 2018, ExchangeWire

GeoSpock’s extreme-scale data mission in $5.4m funding boost
8 October 2020, Cambridge Independent

provided by Google News

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here