Cattle DB

Fast Time Series Database Implementation.

CattleDB can store timeseries data in typical cloud noSQL databases. At the moment bigtable and dynamodb storage backends are implemented. Data can be queried by time ranges very efficiently.

CattleDB can be used as a library in projects or as a standalone service with a REST/gRPC backend to put/get data.

Installation

Recursive Option is needed to build the C Speedups.

git clone --recursive https://github.com:wuttem/cattledb.git
pip install ./cattledb

Run Docker Emulator for Tests on Machine

docker run -it -p 8080:8080 spotify/bigtable-emulator:latest
export BIGTABLE_EMULATOR_HOST=localhost:8080
pytest tests

Build and Start Tests in docker

docker build . -t cattledb-test
docker run -it cattledb-test bash
service bigtable-server start
export BIGTABLE_EMULATOR_HOST="localhost:8080"
pytest tests

Compile python protobuf file

# RUN
python -m grpc.tools.protoc --python_out=./cattledb/grpcserver --grpc_python_out=./cattledb/grpcserver --proto_path=./protos cdb.proto
# cd to .\cattledb\grpcserver\cdb_pb2_grpc.py
# change line
import cdb_pb2 as cdb__pb2
# to
from . import cdb_pb2 as cdb__pb2

Build and Push cattledb docker

docker build . -t mths/cattledb:latest
docker tag mths/cattledb:latest mths/cattledb:0.1
docker push mths/cattledb

Development Build / Upload

python setup.py sdist
twine upload dist/*