DBMS > BoltDB vs. DolphinDB vs. Elasticsearch vs. Fujitsu Enterprise Postgres vs. Google BigQuery

System Properties Comparison BoltDB vs. DolphinDB vs. Elasticsearch vs. Fujitsu Enterprise Postgres vs. Google BigQuery

Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

Large scale data warehouse service with append-only tables

Primary database model

Key-value store

Time Series DBMS
Vector DBMS

Search engine

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS
Vector DBMS

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.70
Rank	#225	Overall
	#31	Key-value stores

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	128.79
Rank	#8	Overall
	#1	Search engines

Score	0.22
Rank	#304	Overall
	#137	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Website

github.com/boltdb/bolt

www.dolphindb.com

www.elastic.co/elasticsearch

www.postgresql.fastware.com

cloud.google.com/bigquery

Technical documentation

docs.dolphindb.cn/en/help200/index.html

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

www.postgresql.fastware.com/product-manuals

cloud.google.com/bigquery/docs

Developer

DolphinDB, Inc

Elastic

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Google

Initial release

2013

2018

2010

Current release

v2.00.4, January 2022

8.6, January 2023

Fujitsu Enterprise Postgres 14, January 2022

License

Commercial or Open Source

Open Source

MIT License

commercial

free community version available

Open Source

Elastic License

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Windows

All OS with a Java VM

Linux
Windows

hosted

Data scheme

schema-free

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP/JSON API

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

partitioning by range, list and by hash

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

ACID

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Memcached and Redis integration

User concepts

Access control

Administrators, Users, Groups

fine grained access rights according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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