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DBMS > Apache Impala vs. Badger vs. CockroachDB vs. Dragonfly vs. TimescaleDB

System Properties Comparison Apache Impala vs. Badger vs. CockroachDB vs. Dragonfly vs. TimescaleDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonBadger  Xexclude from comparisonCockroachDB  Xexclude from comparisonDragonfly  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSKey-value storeRelational DBMSKey-value storeTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.22
Rank#320  Overall
#47  Key-value stores
Score5.73
Rank#58  Overall
#34  Relational DBMS
Score0.49
Rank#261  Overall
#38  Key-value stores
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websiteimpala.apache.orggithub.com/­dgraph-io/­badgerwww.cockroachlabs.comgithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
www.timescale.com
Technical documentationimpala.apache.org/­impala-docs.htmlgodoc.org/­github.com/­dgraph-io/­badgerwww.cockroachlabs.com/­docswww.dragonflydb.io/­docsdocs.timescale.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDGraph LabsCockroach LabsDragonflyDB team and community contributorsTimescale
Initial release20132017201520232017
Current release4.1.0, June 202224.1.0, May 20241.0, March 20232.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache 2.0, commercial license availableOpen Source infoBSL 1.1Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++GoGoC++C
Server operating systemsLinuxBSD
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
LinuxLinux
OS X
Windows
Data schemeyesschema-freedynamic schemascheme-freeyes
Typing infopredefined data types such as float or dateyesnoyesstrings, hashes, lists, sets, sorted sets, bit arraysnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonononoyes
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes, wire compatible with PostgreSQLnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
JDBCProprietary protocol infoRESP - REdis Serialization ProtocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBCGoC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoLuauser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnononopublish/subscribe channels provide some trigger functionalityyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneMulti-source replication using RAFTSource-replica replicationSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencynoneImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDAtomic execution of command blocks and scriptsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, strict serializability by the serveryes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoRole-based access controlPassword-based authenticationfine grained access rights according to SQL-standard

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More resources
Apache ImpalaBadgerCockroachDBDragonflyTimescaleDB
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