DBMS > Apache Impala vs. Axibase vs. HarperDB vs. ObjectBox vs. TerarkDB

System Properties Comparison Apache Impala vs. Axibase vs. HarperDB vs. ObjectBox vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Extremely fast embedded database for small devices, IoT and Mobile

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Document store

Time Series DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

impala.apache.org

axibase.com/docs/atsd/finance

www.harperdb.io

objectbox.io

github.com/bytedance/terarkdb

Technical documentation

impala.apache.org/impala-docs.html

docs.harperdb.io/docs

docs.objectbox.io

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Axibase Corporation

HarperDB

ObjectBox Limited

ByteDance, originally Terark

Initial release

2013

2017

2016

Current release

4.1.0, June 2022

15585

3.1, August 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

free community edition available

Open Source

Apache License 2.0

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Java

Node.js

C and C++

C++

Server operating systems

Linux

Linux
OS X

Android
iOS
Linux
macOS
Windows

Data scheme

yes

dynamic schema

yes

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

JSON data types

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

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

SQL-like data manipulation statements

APIs and other access methods

JDBC
ODBC

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Proprietary native API

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
PHP
Python
R
Ruby

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Custom Functions

since release 3.1

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

A table resides as a whole on one (or more) nodes in a cluster

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

yes

the nodes on which a table resides can be defined

online/offline synchronization between client and server

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Access rights for users and roles

yes

More information provided by the system vendor

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More resources

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