DBMS > Elasticsearch vs. NuoDB vs. QuestDB
System Properties Comparison Elasticsearch vs. NuoDB vs. QuestDB
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|Editorial information provided by DB-Engines|
|Name||Elasticsearch Xexclude from comparison||NuoDB Xexclude from comparison||QuestDB Xexclude from comparison|
|Description||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||NuoDB is a webscale distributed database that supports SQL and ACID transactions||A high performance open source SQL database for time series data|
|Primary database model||Search engine||Relational DBMS||Time Series DBMS|
|Secondary database models||Document store|
|Developer||Elastic||NuoDB, Inc.||QuestDB Limited|
|Current release||8.6, January 2023|
|License Commercial or Open Source||Open Source Elastic License||commercial limited edition free||Open Source Apache 2.0|
|Cloud-based only Only available as a cloud service||no||no||no|
|DBaaS offerings (sponsored links) Database as a Service|
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|Server operating systems||All OS with a Java VM||hosted Amazon EC2, Windows Azure, SoftLayer|
|Data scheme||schema-free Flexible type definitions. Once a type is defined, it is persistent||yes||yes schema-free via InfluxDB Line Protocol|
|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 All search fields are automatically indexed||yes||no|
|SQL Support of SQL||SQL-like query language||yes||SQL-like query language|
|APIs and other access methods||Java API|
RESTful HTTP/JSON API
InfluxDB Line Protocol (TCP/UDP)
|Supported programming languages||.Net|
Community Contributed Clients
|C PostgreSQL driver|
Rust over HTTP
|Server-side scripts Stored procedures||yes||Java, SQL||no|
|Triggers||yes by using the 'percolation' feature||yes||no|
|Partitioning methods Methods for storing different data on different nodes||Sharding||data is dynamically stored/cached on the nodes where it is read/written||horizontal partitioning (by timestamps)|
|Replication methods Methods for redundantly storing data on multiple nodes||yes||yes Managed transparently by NuoDB||Configurable consistency for N replicas|
|MapReduce Offers an API for user-defined Map/Reduce methods||ES-Hadoop Connector||no||no|
|Consistency concepts Methods to ensure consistency in a distributed system||Eventual Consistency Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all||Immediate Consistency||Immediate Consistency|
|Foreign keys Referential integrity||no||yes||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||no||ACID tunable commit protocol||ACID for single-table writes|
|Concurrency Support for concurrent manipulation of data||yes||yes MVCC||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 Temporary table||yes through memory mapped files|
|User concepts Access control||Standard SQL roles/ privileges, Administrative Users|
|More information provided by the system vendor|
|Specific characteristics||Relational model with native time series support Column based storage and time partitioned...|
|Competitive advantages||Real-time data ingestion and istant SQL queries for time series High performance...|
|Typical application scenarios||Application metrics Financial market data and algo trading DevOps monitoring Real-time...|
|Licensing and pricing models||Apache 2.0.|
Getting Started with QuestDB Cloud
Exploring Financial Tick Data with Jupyter Notebook and Pandas
Time-Series Data Visualization with Apache Superset and QuestDB
Optimizing the Optimizer: the Time-Series Benchmark Suite
QuestDB 7.1.2 Release
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