DBMS > Dgraph vs. Elasticsearch vs. Kinetica
System Properties Comparison Dgraph vs. Elasticsearch vs. Kinetica
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|Editorial information provided by DB-Engines|
|Name||Dgraph Xexclude from comparison||Elasticsearch Xexclude from comparison||Kinetica Xexclude from comparison|
|Description||Distributed and scalable native Graph DBMS||A distributed, RESTful modern search and analytics engine based on Apache Lucene Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric||Fully vectorized database across both GPUs and CPUs|
|Primary database model||Graph DBMS||Search engine||Relational DBMS|
|Secondary database models||Document store|
Time Series DBMS
|Developer||Dgraph Labs, Inc.||Elastic||Kinetica|
|Current release||8.6, January 2023||7.1, August 2021|
|License Commercial or Open Source||Open Source Apache 2.0||Open Source Elastic License||commercial|
|Cloud-based only Only available as a cloud service||no||no||no|
|DBaaS offerings (sponsored links) Database as a Service|
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|Implementation language||Go||Java||C, C++|
|Server operating systems||Linux|
|All OS with a Java VM||Linux|
|Data scheme||schema-free||schema-free Flexible type definitions. Once a type is defined, it is persistent||yes|
|Typing predefined data types such as float or date||yes||yes||yes|
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.||no||no||no|
|Secondary indexes||yes||yes All search fields are automatically indexed||yes|
|SQL Support of SQL||no||SQL-like query language||SQL-like DML and DDL statements|
|APIs and other access methods||GraphQL query language|
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
RESTful HTTP API
|Supported programming languages||C#|
Community Contributed Clients
|Server-side scripts Stored procedures||no||yes||user defined functions|
|Triggers||no||yes by using the 'percolation' feature||yes triggers when inserted values for one or more columns fall within a specified range|
|Partitioning methods Methods for storing different data on different nodes||yes||Sharding||Sharding|
|Replication methods Methods for redundantly storing data on multiple nodes||Synchronous replication via Raft||yes||Source-replica replication|
|MapReduce Offers an API for user-defined Map/Reduce methods||no||ES-Hadoop Connector||no|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency||Eventual Consistency Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all||Immediate Consistency or Eventual Consistency depending on configuration|
|Foreign keys Referential integrity||no||no||yes|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID||no||no|
|Concurrency Support for concurrent manipulation of data||yes||yes||yes|
|Durability Support for making data persistent||yes||yes||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||Memcached and Redis integration||yes GPU vRAM or System RAM|
|User concepts Access control||no Planned for future releases||Access rights for users and roles on table level|
|More information provided by the system vendor|
|Specific characteristics||Native and fully vectorized database across both GPUs and CPUs, with memory first...|
|Competitive advantages||Best in class geospatial and temporal analytics. Lockless architecture provides real-time...|
|Typical application scenarios||Any application requiring (1) real time insights, (2) time series analysis (3) geospatial...|
|Key customers||Citibank, US Air Force, Softbank, OVO, Telkomsel, USPS, 2 of the top 3 US Telcos,...|
|Market metrics||The largest IoT deployment in the world, NORAD, runs on Kinetica.|
|Licensing and pricing models||Always Free Tier in the Cloud, Pay-As-You-Go Consumption Based Pricing, and Portable...|
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